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  • Birmingham, UK : Packt Publishing  (263)
  • London : Routledge  (168)
  • Python (Computer program language)  (263)
  • Großbritannien  (168)
Material
Language
  • 1
    ISBN: 9781804613788 , 1804613789 , 9781804610541
    Language: English
    Pages: 1 online resource (398 pages) , illustrations
    Parallel Title: Erscheint auch als
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Machine learning ; Computer programming ; Python (Langage de programmation) ; Apprentissage automatique ; Programmation (Informatique) ; computer programming
    Abstract: Take your data preparation, machine learning, and GenAI skills to the next level by learning a range of Python algorithms and tools for data labeling Key Features Generate labels for regression in scenarios with limited training data Apply generative AI and large language models (LLMs) to explore and label text data Leverage Python libraries for image, video, and audio data analysis and data labeling Purchase of the print or Kindle book includes a free PDF eBook Book Description Data labeling is the invisible hand that guides the power of artificial intelligence and machine learning. In today's data-driven world, mastering data labeling is not just an advantage, it's a necessity. Data Labeling in Machine Learning with Python empowers you to unearth value from raw data, create intelligent systems, and influence the course of technological evolution. With this book, you'll discover the art of employing summary statistics, weak supervision, programmatic rules, and heuristics to assign labels to unlabeled training data programmatically. As you progress, you'll be able to enhance your datasets by mastering the intricacies of semi-supervised learning and data augmentation. Venturing further into the data landscape, you'll immerse yourself in the annotation of image, video, and audio data, harnessing the power of Python libraries such as seaborn, matplotlib, cv2, librosa, openai, and langchain. With hands-on guidance and practical examples, you'll gain proficiency in annotating diverse data types effectively. By the end of this book, you'll have the practical expertise to programmatically label diverse data types and enhance datasets, unlocking the full potential of your data. What you will learn Excel in exploratory data analysis (EDA) for tabular, text, audio, video, and image data Understand how to use Python libraries to apply rules to label raw data Discover data augmentation techniques for adding classification labels Leverage K-means clustering to classify unsupervised data Explore how hybrid supervised learning is applied to add labels for classification Master text data classification with generative AI Detect objects and classify images with OpenCV and YOLO Uncover a range of techniques and resources for data annotation Who this book is for This book is for machine learning engineers, data scientists, and data engineers who want to learn data labeling methods and algorithms for model training. Data enthusiasts and Python developers will be able to use this book to learn data exploration and annotation using Python libraries. Basic Python knowledge is beneficial but not necessary to get started.
    Note: Includes index
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  • 2
    ISBN: 9780367553173 , 9780367553197
    Language: English
    Pages: xiii, 299 Seiten
    Series Statement: ICLARS series on law and religion
    Parallel Title: Erscheint auch als Duddington, John The church and employment law
    DDC: 344.4101
    Keywords: Religious institutions Employees ; Legal status, laws, etc ; Church employees Legal status, laws, etc ; Clergy Legal status, laws, etc ; Großbritannien ; Arbeitsrecht ; Kirche ; Arbeitnehmer ; Rechtsstellung
    Abstract: "This book examines the current law on the employment status of ministers of religion and suggests reforms in this area of the law to meet the need for ministers to be given a degree of employment protection. The work considers the constant theme in Christian history that the clergy should not be subject to the ordinary courts and asks whether this is justified with the growth of areas such as employment law. The work questions whether it is possible to arrive at a satisfactory definition of who is a minister of religion and, along with this, who would be the employer of the minister if there was a contract of employment. Taking a comparative perspective, it evaluates the case law on the employment status of Christian and non-Christian clergy and assesses whether this shows any coherent theme or line of development. The work also considers the issue of ministerial employment status against the background of the autonomy of churches and other religious bodies from the State, together with their ecclesiology. The book will be of interest to academics and researchers working in the areas of law and religion, employment law and religious studies, together with both legal practitioners and human resources practitioners in these areas"--
    Description / Table of Contents: Volunteers -- Religious workers -- The clergy as ministers of religion -- Employment status of the clergy : a comparative perspective -- How can the employment relationship between a member of the clergy and their religious body be analysed? -- The legal status of the clergy under employment law as employees and workers -- The autonomy of religious bodies -- The perspectives of churches on the legal status of the clergy and other religious workers -- A solution? : potential reforms to achieve a degree of employment protection for clergy and other religious workers.
    Note: Includes bibliographical references and index
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  • 3
    ISBN: 9781032146263 , 9781032146256
    Language: English
    Pages: 164 Seiten , Illustrationen
    DDC: 303.3
    Keywords: Außenhandel ; Soziale Gerechtigkeit ; Sozialer Wandel ; USA ; Großbritannien
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  • 4
    ISBN: 9780367720568 , 9780367722159
    Language: English
    Pages: x, 220 Seiten
    Parallel Title: Erscheint auch als Renton, Dave, 1972- Labour's antisemitism crisis
    DDC: 305.892/4041
    RVK:
    Keywords: Labour Party (Great Britain) ; Antisemitism Political aspects ; Right and left (Political science) ; Great Britain Politics and government 2007- ; Livingstone, Ken 1945- ; Corbyn, Jeremy 1949- ; Antisemitismus ; Labour Party ; Großbritannien ; Antizionismus ; Antisemitismus ; Die Linke
    Abstract: "Between 2015 and 2020 the Labour Party was riven by allegations that the party had tolerated antisemitism. For the Labour right, and some in the media, the fact that such allegations could be made was proof of a moral collapse under Jeremy Corbyn's leadership. Sections of the left meanwhile, sought to resist the accusations by claiming that the numbers of people accused of racism were few, that the allegations were an orchestrated attack, and that those found guilty were excluded from the party. This important book by one of Britain's leading historians of anti-fascism gives a more detailed account than any yet published of what went wrong in Labour. Renton rejects those on the right who sought to exploit the issue for factional advantage. He also criticises those of his comrades on the left who were ignorant about what most British Jews think and demonstrated a willingness to antagonise them. This book will appeal to anyone who cares about antisemitism or left-wing politics"--
    Note: Includes bibliographical references and index
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  • 5
    ISBN: 9780367440961
    Language: English
    Pages: viii, 315 Seiten , Illustrationen
    Series Statement: Routledge studies in cultural history
    DDC: 398.20941
    RVK:
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    Keywords: Nation ; Volkskultur ; Großbritannien ; Irland
    Note: Includes bibliographical references and index.
    URL: Cover  (lizenzpflichtig)
    URL: Cover  (lizenzpflichtig)
    URL: Cover  (lizenzpflichtig)
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  • 6
    ISBN: 9781138300835
    Language: English
    Pages: 108 Seiten , Illustrationen
    Parallel Title: Erscheint auch als Wincott, Abigail Growing heritage
    DDC: 306
    Keywords: Großbritannien ; Landwirtschaft ; Gemüse ; Frucht
    Abstract: This book is the first comprehensive critical analysis of the cultural politics of a new kind of British heritage discourse. Based on texts ranging from tweets to restaurant menus that tell the story of heritage vegetables, this book explores what it means to think about our food systems, and their future, through the lens of 'heritage'. From town hall seed swaps to restaurant menus and coffee table books, it has become hard in recent years for consumers to avoid the idea of 'heritage' fruit and vegetables. The British counterpart of North American heirlooms, their varied colours, strange shapes and endearing names are charming. Yet their proponents claim far more for them, arguing it is vital that we safeguard our crop heritage for global food security, social justice and consumer choice. This book examines how heritage fruits and vegetables are adopted to subvert corporate food production and take food back into our own hands, while supermarkets are eagerly adding them to their luxury ranges. The book also discusses the practice of heritage seeds being stored in secure facilities where most of the world's growers cannot reach them. Written in an accessible style, this book will appeal to those studying, and those interested in, food studies and food politics; heritage studies; geography and environmental studies; the sociology of consumption and cultural studies
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  • 7
    Book
    Book
    London : Routledge
    ISBN: 9781138492516 , 9781138492523
    Language: English
    Pages: xiii, 348 Seiten , Illustrationen
    Edition: Third edition
    Parallel Title: Erscheint auch als Tallon, Andrew Urban regeneration in the UK
    DDC: 307.3/4160941
    RVK:
    RVK:
    Keywords: City planning ; Urban policy ; Großbritannien ; Stadtsanierung
    Abstract: "The textbook provides a comprehensive and critical synthesis of urban regeneration in the UK incorporating key philosophies, approaches, policies, issues, debates and overall critiques from the 1940s up until the late 2010s. The central objective is to place the historical and contemporary regeneration agenda into context. The major changes to the new edition are that the urban agenda and changes to regeneration policies under the Coalition government/Conservative government of the period 2010-2017 are assessed, as well as the influences of economic uncertainty, austerity and Brexit. Advances in the academic literature, policy, and city case studies are also incorporated"--
    Note: Literaturangaben , Includes bibliographical references and index
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  • 8
    ISBN: 9780367725228 , 9780367725143
    Language: English
    Pages: xvi, 210 Seiten , Illustrationen
    Parallel Title: Erscheint auch als Williamson, Howard The milltown boys at sixty
    DDC: 305.5/6909429
    Keywords: Poor Longitudinal studies ; Poor men Case studies ; Großbritannien ; Armut ; Mann
    Abstract: "The Milltown Boys at Sixty is a story like no other, giving both an insider and an outsider view of the 'Milltown Boys', exploring the nature of an ethnographic relationship based on research about their experiences of the criminal justice system. A group classically labelled as delinquents, drug-takers and drop-outs, the Boys were also, in many different ways, fathers, friends and family men, differentially immersed in the labour market, in very different family relationships and now very differently connected to criminal activity. Williamson has written books capturing their experiences over the fifty years of his continued association with them: about their teenage years; and twenty years later, in middle-age. This book is about them as they pass the age of 60, providing a personal account of the relationship between Williamson and the Boys, and the distinctive - perhaps even controversial - research methodology that enabled the mapping of their lives. It provides a unique and detailed insight into the ways in which the lives of the Milltown Boys that started with such shared beginnings have unfolded in so many diverse and fascinating ways. These accounts will be of interest to the lay reader curious about the way others have managed (or failed to manage) their lives, the professional who works with those living, often struggling, on the wrong side of the tracks, and the academic researching and teaching about social exclusion, substance misuse, criminal justice transitions and the life course"--
    Note: Includes bibliographical references and index
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  • 9
    ISBN: 9780367628987 , 9780367628956
    Language: English
    Pages: xiii, 226 Seiten , Illustrationen
    Parallel Title: Erscheint auch als COVID-19 crisis
    Parallel Title: Erscheint auch als The COVID-19 crisis
    DDC: 362.1962/414
    Keywords: Coronavirus ; Gesellschaft ; Lockdown ; Gesundheitsversorgung ; Soziale Folgen ; Soziale Beziehungen ; Soziale Gruppe ; Soziale Ausgrenzung ; Australien ; EU-Staaten ; Großbritannien ; Neuseeland ; Nordamerika ; Südafrika ; COVID-19 (Disease) Social aspects ; Public health Social aspects ; Epidemics Social aspects ; Fallstudie ; Aufsatzsammlung ; COVID-19 ; Pandemie ; Krise ; Gesellschaft
    Abstract: "Since its emergence in early 2020, the COVID-19 crisis has affected every part of the world. Well beyond its health effects, the pandemic has wrought major changes in people's everyday lives as they confront restrictions imposed by physical distancing and consequences such as loss of work, working or learning from home and reduced contact with family and friends. This edited collection covers a diverse range of experiences, practices and representations across international contexts and cultures (UK, Europe, North America, South Africa, Australia and New Zealand). Together, these contributions offer a rich account of COVID society. They provide snapshots of what life was like for people in a variety of situations and locations living through the first months of the novel coronavirus crisis, including discussion not only of health-related experiences but also the impact on family, work and social life and leisure activities. The socio-material dimensions of quotidian practices are highlighted: death rituals, dating apps, online musical performances, fitness and exercise practices, the role of windows, healthcare work, parenting children learning at home, moving in public space as a blind person and many more diverse topics are explored. In doing so, the authors surface the feelings of strangeness and challenges to norms of practice that were part of many people's experiences, highlighting the profound affective responses that accompanied the disruption to usual cultural forms of sociality and ritual in the wake of the COVID outbreak and restrictions on movement. The authors show how social relationships and social institutions were suspended, re-invented or transformed while social differences were brought to the fore. At the macro-level, the book includes localised and comparative analyses of political, health system and policy responses to the pandemic and highlights the differences in representations and experiences of very different social groups, including people with disabilities, LGBTQI people, Dutch Muslim parents, healthcare workers in France and Australia, young adults living in Northern Italy, performing artists and their audiences, exercisers in Australia and New Zealand, the Latin cultures of Spain and Italy, Asian-Americans and older people in Australia. This volume will appeal to undergraduates and postgraduates in sociology, cultural and media studies, medical humanities, anthropology, political science and cultural geography."
    Note: Literaturangaben
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  • 10
    ISBN: 9781138340299
    Language: English
    Pages: xvii, 262 Seiten
    Series Statement: ICLARS series on law and religion
    Parallel Title: Erscheint auch als Topidi, Kyriaki Law and religious diversity in education
    DDC: 344/.07
    Keywords: Religion in the public schools Law and legislation ; Religious minorities Legal status, laws, etc ; Multiculturalism Law and legislation ; Religion in the public schools Law and legislation ; Religion in the public schools L aw and legislation ; Religion in the public schools Law and legislation ; Großbritannien ; Israel ; Religionsunterricht ; Multikulturelle Gesellschaft ; Recht
    Abstract: The method : legal pluralism and comparative constitutional law : complementary methodology in the protection of religious difference -- The concepts : religious diversity within multicultural classrooms: religious freedom, education and equality -- The standards : interpreting the legal interaction of religious freedom, education and non-discrimination in international law -- Plural public education in Israel : for equal or different learners? -- Avoiding religion? : the question of religious identity conflicts in South African public education -- From tradition to modernity and back : religious diversity in English schools as a test-case for multicultural societies -- Negotiating religious identity in public classrooms legal empowerment through religious diversity in schools.
    Abstract: "Religion is a prominent legal force despite the premise constructed and promoted by Western constitutionalism that it must be separated from the State in democracies. Education constitutes an area of human life that leaves ample scope for the expression of religious identity and shapes the citizens of the future. It is also the place of origin of a considerable number of normative conflicts involving religious identity that arise today in multicultural settings. The book deals with the interplay of law and religion in education through the versatility of religious law, legal pluralism, as well as religion's possible adaptation and reconciliation with modernity, in order to consider and reflect on normative conflicts. It adopts the angle of the constitutional dimension of religion narrated in a comparative perspective and critically reflects on regulatory attempts by the state and the international community to promote new ways of living together"--
    Note: Includes bibliographical references and index
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  • 11
    Online Resource
    Online Resource
    London : Routledge
    ISBN: 9781000172300 , 9780429355486
    Language: English
    Pages: 1 Online-Ressource (239 Seiten)
    Series Statement: Routledge new religions
    Parallel Title: Erscheint auch als Cottrell-Boyce, Aidan Israelism in modern Britain
    DDC: 303.48/24105694
    Keywords: Electronic books ; Großbritannien ; Israelischer Einwanderer ; Israel
    Abstract: Cover -- Half Title -- Series -- Title -- Copyright -- Contents -- Introduction -- 1 What do British-Israelists believe? -- 2 A history of British-Israelism in the twentieth century -- 3 British-Israelism and the Jews -- 4 British-Israelism and the British Empire -- 5 British-Israelism and Ireland -- 6 British-Israelism and the state of Israel -- 7 British-Israelism and Russia -- 8 British-Israelism and the European Union -- Conclusion -- Select bibliography -- Index.
    Note: Description based on publisher supplied metadata and other sources
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  • 12
    ISBN: 9780367516819
    Language: English
    Pages: xvii, 229 Seiten , Illustrationen
    Series Statement: Routledge studies in Asian diasporas, migrations and mobilities 5
    Series Statement: Routledge studies in Asian diasporas, migrations and mobilities
    Parallel Title: Erscheint auch als Belford, Nish Asian Women, Identity and Migration
    Parallel Title: Erscheint auch als Asian women, identity and migration
    DDC: 305.48/8914041
    Keywords: Women, East Indian Social conditions ; Women, East Indian Social conditions ; East Indians Social conditions ; East Indians Social conditions ; Women, East Indian Ethnic identity ; Women, East Indian Race identity ; East Indian diaspora ; Transnationalism ; Immigrants Social conditions ; Immigrants Social conditions ; Aufsatzsammlung ; Australien ; Großbritannien ; Südasiatin ; Soziale Identität ; Diaspora
    Abstract: "This book explores the influence which education and migration experiences have on women of Indian origin in Australia and the United Kingdom when (re)-negotiating their identities. The intersections of migration and transnationalism are critically examined through multiple theoretical lenses across three thematic domains encompassing socio-historical discourses, postcolonial theory, theories on intersectionality and interceptionality, emotional reflexivity and affects. In doing so, the book highlights the ambiguities around gendered access and equity to education, migration experiences, the acculturation process, dilemmas surrounding transnationality and negotiation of identities, belonging and struggles inherent in simultaneously maintaining ties with home and new social fields. Chapters highlight the practical, methodological, and substantive aspects of affective dimensions and voice with a critical understanding of different tensions, challenges, complexities and conflicts underlining the stories. The book raises the question of voice and agency in advocating emotion-based writing in recalibrating conditions representing gendered subjective multivocality of women in breaking silences. Presenting non-Western perspectives through fragmented and often marginalised accounts within transnational and global spaces, this book will be of interest to researchers in the fields of Sociology, Gender Studies, Migration, Transnational and Diaspora studies, Sociology of Education, Feminist Studies, Cultural Studies, Literature and Cultural Geographies"--
    Note: Includes bibliographical references and index
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  • 13
    ISBN: 9780815347163 , 0815347162
    Language: English
    Pages: xxii, 184 Seiten , Illustrationen , 24 cm
    Series Statement: Routledge research in education
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als Lowe, Roy Schooling and social change since 1760
    DDC: 306.43209042
    Keywords: Geschichte 1760-2020 ; Education Social aspects ; History ; Schule ; Bildung ; Sozialer Wandel ; Education ; Social aspects ; Informational works ; History ; Informational works ; Großbritannien ; England
    Abstract: Schooling and Social Change in England since 1760 offers a powerful critique of the situation of British education today and shows the historical processes that have helped generate the crisis confronting policymakers and practitioners at the present time. The book identifies the key phases of economic and social change since 1760 and shows how the education system has played a central role in embedding, sustaining and deepening social distinctions in Britain. Covering the whole period since the first industrialization, it gives a detailed account of the development of a deeply divided education system that leads to quite separate lifestyles for those from differing backgrounds. The book develops arguments of inequalities through a much-needed account of the changes in education. This book will be of great interest for academics, scholars and post-graduate students in the field of history of education and education politics. It will also appeal to administrators, teachers and policy makers, especially those interested in the historical development of schooling
    Note: Includes bibliographical references and index
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  • 14
    ISBN: 9781138561793
    Language: English
    Pages: xi, 266 Seiten , Illustrationen , 24 cm
    Series Statement: Routledge Hindu studies series
    DDC: 294.5512095414
    RVK:
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    Keywords: Kolonialismus ; Vishnuismus ; Caitanya-Gemeinde ; Baul ; Großbritannien ; Bengalen ; Britisch-Indien ; Aufsatzsammlung ; Aufsatzsammlung ; Aufsatzsammlung
    Note: War angekündigt unter dem Titel: Hinduism in colonial Bengal : beyond the Renaissance , Literaturangaben und Index
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  • 15
    ISBN: 9781409405795
    Language: English
    Pages: x, 191 Seiten , Illustrationen , 26 cm
    Additional Information: Basiert auf Westgarth, Mark The emergence of the antique and curiosity dealer 1815-c. 1850 Southampton : University of Southampton, 2006 Dissertation, University of Southampton, 2006
    Series Statement: The histories of material culture and collecting, 1700-1950
    Parallel Title: Erscheint auch als Westgarth, Mark The emergence of the antique and curiosity dealer in Britain 1815-1850
    DDC: 745.10941
    RVK:
    Keywords: Isaac, John Coleman ; Art and society History 19th century ; Antiques business History 19th century ; Great Britain Commerce 19th century ; History ; Isaac, John Coleman 1803-1887 ; Kunsthandel ; Großbritannien ; Kunsthandel ; Antiquitätenhandel ; Geschichte 1815-1850
    Abstract: "Rather than the customary focus on the activities of individual collectors, The Emergence of the Antique and Curiosity Dealer in Britain 1815-1850: The Commodification of Historical Objects illuminates the less-studied roles played by dealers in the nineteenth-century antique and curiosity markets. Set against the recent 'art market turn' in scholarly literature, this volume examines the role, activities, agency and influence of antique and curiosity dealers as they emerged in the opening decades of the nineteenth century. This study begins at the end of the Napoleonic Wars, when dealers began their wholesale importations of historical objects; it closes during the 1850s, after which the trade became increasingly specialized, reflecting the rise of historical museums such as the South Kensington Museum (V&A). Focusing on the archive of the early-nineteenth-century London dealer John Coleman Isaac (c.1803-1887), as well as drawing on a wide range of other archival and contextual material, Mark Westgarth considers the emergence of the dealer in relation to a broad historical and cultural landscape. The emergence of the antique and curiosity dealer was part of the rapid economic, social, political and cultural change of early-nineteenth-century Britain, centered around ideas of antiquarianism, the commercialization of culture, and a distinctive and evolving interest in historical objects. This book will be of interest to scholars in art history, histories of collecting, museum and heritage studies, and nineteenth century culture"--
    Note: "This book [...] evolved from my PhD thesis (University of Southampton, 2007) of the same title, under the supervision of Dana Arnold [...]." (Acknowledgements, Seite [ix]) , Vollständige bibliografische Daten der Dissertation: Westgarth, Mark: The emergence of the antique and curiosity dealer 1815-c. 1850 : the commodification of historical objects / Mark Wilfred Westgarth. Southampton : University of Southampton, 2006. 1 Band ; 31 cm. Dissertation, University of Southampton, 2006 , Literaturverzeichnis Seite [162]-181 , Mit Register
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  • 16
    ISBN: 9781003135647
    Language: English
    Pages: 1 Online Ressource (xiv, 171 Seiten) , Illustrationen
    Parallel Title: Erscheint auch als
    DDC: 306.7/0942
    RVK:
    Keywords: Geschichte 1832-1902 ; PSYCHOLOGY / Human Sexuality (see also SOCIAL SCIENCE / Human Sexuality) ; Photography of women History 19th century ; Photography, Erotic ; Sex in art ; Sex role History 19th century ; Sex History 19th century ; Sexualität ; Fotografie ; Großbritannien ; Großbritannien ; Fotografie ; Sexualität ; Geschichte 1832-1902
    Abstract: An intimate look into three Victorian photo-settings, Pleasures Taken considers questions of loss and sexuality as they are raised by some of the most compelling and often misrepresented photographs of the era: Lewis Carroll's photographs of young girls; Julia Margaret Cameron's photographs of Madonnas; and the photographs of Hannah Cullwick, a "maid of all work," who had herself pictured in a range of masquerades, from a blackened chimney sweep to a bare-chested Magdalene. Reading these settings performatively, Carol Mavor shifts the focus toward the subjectivity of these girls and women, and toward herself as a writer.Mavor's original approach to these photographs emphatically sees sexuality where it has been previously rendered invisible. She insists that the sexuality of the girls in Carroll's pictures is not only present, but deserves recognition, respect, and scrutiny. Similarly, she sees in Cameron's photographs of sensual Madonnas surprising visions of motherhood that outstrip both Victorian and contemporary understandings of the maternal as untouchable and inviolate, without sexuality. Finally she shows how Hannah Cullwick, posing in various masquerades for her secret paramour, emerges as a subject with desires rather than simply a victim of her upper-class partner. Even when confronting the darker areas of these photographs, Mavor perseveres in her insistence on the pleasures taken-by the viewer, the photographer, and often by the model herself-in the act of imagining these sexualities. Inspired by Roland Barthes, and drawing on other theorists such as Julia Kristeva and Luce Irigaray, Mavor creates a text that is at once interdisciplinary, personal, and profoundly pleasurable
    Note: Description based on online resource; title from PDF title page (publisher's Web site, viewed 12. Dez 2020) , In English
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 17
    ISBN: 9780367727000 , 9781138052185
    Language: English
    Pages: xxxii, 237 Seiten
    Series Statement: ICLARS series on law and religion
    Dissertation note: Dissertation Chinese University of Hong Kong 2015
    DDC: 342.08/521441
    Keywords: Parent and child (Law) ; Freedom of religion ; Children (International law) ; Parent and child (Law) ; Parent and child (Law) ; Parent and child (Law) ; Freedom of religion ; Freedom of religion ; Freedom of religion ; Hochschulschrift ; Frankreich ; Großbritannien ; Hongkong ; Religionsfreiheit ; Kind ; Grundrecht ; Schiedsgericht
    Abstract: Introduction -- A parental right to impose religious manifestations? -- Children's right to freedom of manifestation -- Coerced manifestations as limitations to rights -- Invoking and enforcing freedom of manifestation within the family -- Parentally coerced religious manifestations in France -- Parentally coerced religious manifestations in England -- Parentally coerced religious manifestations in Hong Kong -- Conclusion.
    Note: Bibliographie: Seite [208]-230
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  • 18
    ISBN: 9780415627306 , 9780415627290
    Language: English
    Pages: xii, 580 Seiten , Illustrationen , 24,5 cm
    Additional Information: Rezensiert in Shaffer, Ryan, 1982 - New approaches to post-war British fascism 2021
    Series Statement: Routledge studies in fascism and the far right
    Parallel Title: Erscheint auch als Macklin, Graham Failed führers
    DDC: 320.53/3
    RVK:
    Keywords: Fascists Biography ; Right-wing extremists Biography ; Right-wing extremists History 20th century ; Fascism History 20th century ; Great Britain Race relations ; Great Britain Politics and government 20th century ; Chesterton, Arthur K. 1899-1973 ; Jordan, Colin 1923-2009 ; Tyndall, John 1934-2005 ; Leese, Arnold 1878-1956 ; Mosley, Oswald 1896-1980 ; Großbritannien ; Rechtsradikalismus ; Geschichte 1918-2020 ; Großbritannien ; Rechtsradikalismus ; Geschichte 1918-2020
    Abstract: Arnold Leese: The 'Anti-Jewish' Camel Doctor -- Sir Oswald Mosley: From 'Britain First' to 'Europe-a-Nation' -- A. K. Chesterton: From 'Fascist revolutionary' to 'Jew-wise' conspiracy theorist -- Colin Jordan: Dreaming of the Nazi 'Vanguard' -- John Tyndall: In pursuit of the 'Anglo-Saxon Reich' -- Nick Griffin: From the 'Third Position' to anti-Muslim 'populism'... and back again.
    Abstract: "This book provides a comprehensive history of the ideas and ideologues associated with the racial fascist tradition in Britain. It charts the evolution of the British extreme right from its post-war genesis after 1918 to its present-day incarnations, and details the ideological and strategic evolution of British fascism through the prism of its principal leaders and the movements with which they were associated. Taking a collective biographical approach, the book focuses on the political careers of six principal ideologues and leaders, Arnold Leese (1878-1956); Sir Oswald Mosley (1896-1980); A. K. Chesterton (1899-1973); Colin Jordan (1923-2009); John Tyndall (1934-2005); and Nick Griffin (1959 -), in order to study the evolution of the racial ideology of British Fascism, from overtly biological conceptions of 'white supremacy' through 'racial nationalism' and latterly to 'cultural' arguments regarding 'ethno-nationalism'. Drawing on extensive archival research and often obscure primary texts and propaganda as well as the official records of the British government and its security services, this is the definitive historical account of Britain's extreme right and will be essential reading for all students and scholars of race relations, extremism and fascism."--
    Note: Literaturverzeichnis: Seite 559-562 , Hier auch später erschienene, unveränderte Nachdrucke
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  • 19
    ISBN: 9781138386068 , 9781138386129
    Language: English
    Pages: xiii, 218 Seiten , Diagramme
    Series Statement: Routledge studies in fascism and the far right
    DDC: 303.48/4
    RVK:
    RVK:
    RVK:
    Keywords: Radicalism ; Political violence ; Right and left (Political science) ; Großbritannien ; Politik ; Gewalt ; Radikalismus ; Geschichte 1967-2020
    Abstract: Fascists and anti-fascists, 1920-1940 -- Fascists and anti-fascists in the 1970s -- Fascists and anti-fascists in the 1980s and 1990s -- Northern Ireland from 1960 to 1976 -- Islamists and the counter-jihad in Britain, 2009-2018.
    Abstract: "This book frames several historical incidents of violent movement-countermovement conflicts within the concept of 'cumulative extremism'- the mutually reinforcing dynamic of radicalisation that can develop between two or more antagonistic groups. Drawing on several in-depth case studies, including the contests between British fascist and anti-fascist groups in the interwar period and from 1967 to 1979 and 1980 to 2000; the Troubles in Northern Ireland from the late 60s to mid-70s; and Islamist extremists and the far-right counter-jihad movement in Britain since 2009, this book presents the first in-depth academic analysis of the concept of 'cumulative extremism' and constructs a theoretical framework through which to assess its development. This is a groundbreaking volume which will be of particular relevance to scholars with an interest in the extreme right, social movements, political violence and criminology. It will also be of interest to policy makers and to practitioners dealing with extremism and radicalisation, including youth workers, Prevent coordinators, community support officers and police officers"--
    Note: Includes bibliographical references and index
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  • 20
    ISBN: 1138087467 , 9781138087460
    Language: English
    Pages: x, 212 Seiten , Illustrationen
    Edition: 1. published
    Series Statement: Routledge critical studies in Buddhism
    RVK:
    Keywords: Großbritannien ; Buddhistin ; Großbritannien ; Buddhismus ; Frau
    Note: Enthält Bibliografie, Anhang und Index
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  • 21
    ISBN: 9781138359567 , 9780367664053
    Language: English
    Pages: xv, 212 Seiten , Illustrationen
    Series Statement: Perspectives on the non-human in literature and culture
    DDC: 304.27
    RVK:
    Keywords: Geschichte 1837-1901 ; Englisch ; Literatur ; Tiere ; Großbritannien
    Note: Literaturangaben
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  • 22
    ISBN: 9781138634916
    Language: English
    Pages: x, 180 Seiten , Diagramme
    Edition: Reissued
    Series Statement: Routledge revivals
    Parallel Title: Erscheint auch als
    Dissertation note: Dissertation Universität Amsterdam 1999
    DDC: 306.8743
    Keywords: Geschichte 1980-1996 ; Work and family Case studies ; Women Case studies Employment ; Working mothers Case studies ; Mutter ; Frauenarbeit ; Berufstätigkeit ; Schweden ; Deutschland ; Großbritannien ; Niederlande ; Hochschulschrift ; Deutschland ; Großbritannien ; Schweden ; Niederlande ; Frauenarbeit ; Mutter ; Berufstätigkeit ; Geschichte 1980-1996
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  • 23
    ISBN: 9780367348106 , 9781138814004
    Language: English
    Pages: x, 216 Seiten , 24 cm
    Series Statement: Routledge advances in critical diversities 5
    Series Statement: Routledge advances in critical diversities
    DDC: 306.76
    RVK:
    RVK:
    Keywords: Sexual minorities Social conditions ; Sexual minorities Identity ; Sexual minority community ; Communities ; Identität ; LGBT ; Gemeinschaft ; Gesellschaft ; Großbritannien ; Großbritannien ; LGBT ; Großbritannien ; LGBT ; Identität ; Gemeinschaft ; Gesellschaft
    Abstract: The phrase LGBT community is often used by policy-makers, service providers, and lesbian, gay, bisexual and trans (LGBT) people themselves, but what does it mean? What understandings and experiences does that term suggest, and ignore? Based on a UK-wide study funded by the Arts and Humanities Research Council, this book explores these questions from the perspectives of over 600 research participants. Examining ideas about community ownership; difference and diversity; relational practices within and beyond physical spaces; imagined communities and belongings; the importance of ritual spaces and symbols, and consequences for wellbeing, the book foregrounds the lived experience of LGBT people to offer a broad analysis of commonalities and divergences in relation to LGBT identities. Drawing on an interdisciplinary perspective grounded in international social science research, the book will appeal to students and scholars with interests in sexual and/or gender identities in the fields of community studies, cultural studies, gender studies, geography, leisure studies, politics, psychology, sexuality studies, social policy, social work, socio-legal studies, and sociology. The book also offers implications for practice, suitable for policy-maker, practitioner, and activist audiences, as well as those with a more personal interest.
    Abstract: Introduction -- "Owning" and questioning LGBT communities -- Diversity, inequality and prejudice amongst LGBT people -- Lived experience and "doing" community -- Relationships to, within and beyond physical spaces -- The pleasures and pains of scene spaces -- Pride spaces, rituals and symbols -- Imagined communities and a sense of belonging -- Consequences for wellbeing -- Conclusions and implications
    Note: Includes bibliographical references and index
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  • 24
    ISBN: 9781472466594
    Language: English
    Pages: xv, 254 Seiten , Illustrationen , 24 cm
    Series Statement: British literature in context in the long eighteenth century
    Parallel Title: Erscheint auch als
    DDC: 395.094109033
    Keywords: Commonwealth ; Geschichte 1700-1850 ; Noise Social aspects 18th century ; History ; Courtesy History 18th century ; Literatur ; Geräusch ; Umgang ; Englisch ; Alltagskultur ; Geräusch ; Großbritannien ; Aufsatzsammlung ; Großbritannien ; Commonwealth ; Geräusch ; Umgang ; Englisch ; Literatur ; Alltagskultur ; Geräusch ; Geschichte 1700-1850
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  • 25
    ISBN: 9781138986756 , 9780415172608
    Language: English
    Pages: xii, 330 Seiten , 24 cm
    Series Statement: Routledge progress in psychology 3
    Series Statement: Routledge progress in psychology
    DDC: 303.6/0941
    RVK:
    Keywords: Violence on television ; Television programs ; Fernsehsendung ; Fernsehen ; Gewalt ; Gewaltdarstellung ; Großbritannien ; Großbritannien ; Fernsehen ; Gewalt ; Großbritannien ; Gewaltdarstellung ; Fernsehsendung
    Note: Includes bibliographical references (p. [304]-316) and indexes
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  • 26
    ISBN: 9780415635868 , 0415635861 , 9780367867393 , 0367867397
    Language: English
    Pages: ix, 259 Seiten
    Edition: First issued in paperback
    Series Statement: Routledge research in gender and history 29
    Series Statement: Routledge research in gender and history
    DDC: 305.420941
    RVK:
    Keywords: Frauenfeindlichkeit ; Schande ; Großbritannien ; Irland ; Australien ; Großbritannien ; Irland ; Australien ; Frauenfeindlichkeit ; Schande ; Geschichte 1890-1920
    Abstract: Inhaltsverzeichnis: Introduction -- Shaming unwomanly women -- Reversing the shame of British colonisation -- Embarrassing the Imperial centre -- Shaming British-Australia -- War and the dishonourable British feminist -- Shaming manhood to embody courage -- The shame of the violent woman -- Conclusion.
    Note: Includes bibliographical references and index. - First published 2018 by Routledge
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  • 27
    ISBN: 9781138223035 , 9781138223028
    Language: English
    Pages: x, 275 Seiten , Illustrationen, Diagramme
    Edition: Second edition
    Series Statement: Communication and society
    DDC: 306.0941
    Keywords: Social change History ; Political culture History ; Social values History ; Conflict of generations Political aspects ; Mass media Political aspects ; New Left History ; New Left Press coverage ; Right and left (Political science) ; Großbritannien ; Zeitung ; Wert ; Generationskonflikt ; Neue Linke ; Geschichte
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  • 28
    ISBN: 9781138299634
    Language: English
    Pages: 189 Seiten
    Series Statement: Routledge studies in extremism and democracy
    Parallel Title: Erscheint auch als Allchorn, William, author Anti-Islamic protest in the UK
    DDC: 305.6/970941
    Keywords: English Defence League ; Britain First (Political party) ; Islamophobia Government policy ; Right-wing extremists Government policy ; Great Britain Politics and government 2007- ; Großbritannien ; Islamfeindlichkeit ; Rechtsradikalismus ; Bekämpfung ; Politik
    Abstract: Introduction: Why policy responses to the EDL and Britain First? -- Context: the rise of anti-Islamic protest and the evolution of the UK far right -- What policy responses? UK national policy responses and localised countermeasures in relation to anti-Islamic protest -- "Where it all began": policy responses to the EDL and Britain first in Luton -- Early responses to anti-Islamic protest: policy responses to the EDL and Britain First in Birmingham -- West Yorkshire's response to anti-Islamic protest: policy responses to the EDL and Britain First in Bradford -- "Somewhere near the Clock Tower": policy responses to the EDL and Britain First in Leicester -- Anti-Islamic protest in London's East end: policy responses to the EDL and Britain First in tower hamlets -- Conclusion: Key findings, recommendations and future responses.
    Abstract: "Demonstrations by far-right groups, such as the English Defence League, Britain First and PEGIDA, have caused considerable social and civic unrest in UK cities for nearly a decade. But how should policymakers respond to far-right and anti-Muslim activism? Drawing on extensive primary research with stakeholders, local authorities and policymakers, this book investigates the political, socio-economic and historic trends that fuel this form of political extremism across the UK. It also maps the different types of policy responses available to local politicians, police forces and behind-the-scenes policy officials involved in the day-to-day management of anti-Islamic street protest. The author demonstrates that it is only through developing successful countermeasures in the realm of politics, security and community-based politics that politicians, police and state actors will truly get to grips with this new far-right activism"--
    Note: Includes bibliographical references and index
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  • 29
    ISBN: 9781838648831 , 1838648836
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: SPARK (Computer program language) ; Application software ; Development ; Big data ; Electronic data processing ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Use PySpark to easily crush messy data at-scale and discover proven techniques to create testable, immutable, and easily parallelizable Spark jobs Key Features Work with large amounts of agile data using distributed datasets and in-memory caching Source data from all popular data hosting platforms, such as HDFS, Hive, JSON, and S3 Employ the easy-to-use PySpark API to deploy big data Analytics for production Book Description Apache Spark is an open source parallel-processing framework that has been around for quite some time now. One of the many uses of Apache Spark is for data analytics applications across clustered computers. In this book, you will not only learn how to use Spark and the Python API to create high-performance analytics with big data, but also discover techniques for testing, immunizing, and parallelizing Spark jobs. You will learn how to source data from all popular data hosting platforms, including HDFS, Hive, JSON, and S3, and deal with large datasets with PySpark to gain practical big data experience. This book will help you work on prototypes on local machines and subsequently go on to handle messy data in production and at scale. This book covers installing and setting up PySpark, RDD operations, big data cleaning and wrangling, and aggregating and summarizing data into useful reports. You will also learn how to implement some practical and proven techniques to improve certain aspects of programming and administration in Apache Spark. By the end of the book, you will be able to build big data analytical solutions using the various PySpark offerings and also optimize them effectively. What you will learn Get practical big data experience while working on messy datasets Analyze patterns with Spark SQL to improve your business intelligence Use PySpark's interactive shell to speed up development time Create highly concurrent Spark programs by leveraging immutability Discover ways to avoid the most expensive operation in the Spark API: the shuffle operation Re-design your jobs to use reduceByKey instead of groupBy Create robust processing pipelines by testing Apache Spark jobs Who this book is for This book is for developers, data scientists, business analysts, or anyone who needs to reliably analyze large amounts of large-scale, real-world data. Whether you're tasked with creating your company's business intelligence function or creating great data platforms for your machine learning models, or are looking to use code to mag...
    Note: Description based on online resource; title from title page (Safari, viewed May 9, 2019)
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  • 30
    ISBN: 9781789533422 , 1789533422
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Application software ; Development ; Cloud computing ; Electronic books ; Electronic books ; local
    Abstract: A practical guide for developing end-to-end serverless microservices in Python for developers, DevOps, and architects. Key Features Create a secure, cost-effective, and scalable serverless data API Use identity management and authentication for a user-specific and secure web application Go beyond traditional web hosting to explore the full range of cloud hosting options Book Description Over the last few years, there has been a massive shift from monolithic architecture to microservices, thanks to their small and independent deployments that allow increased flexibility and agile delivery. Traditionally, virtual machines and containers were the principal mediums for deploying microservices, but they involved a lot of operational effort, configuration, and maintenance. More recently, serverless computing has gained popularity due to its built-in autoscaling abilities, reduced operational costs, and increased productivity. Building Serverless Microservices in Python begins by introducing you to serverless microservice structures. You will then learn how to create your first serverless data API and test your microservice. Moving on, you'll delve into data management and work with serverless patterns. Finally, the book introduces you to the importance of securing microservices. By the end of the book, you will have gained the skills you need to combine microservices with serverless computing, making their deployment much easier thanks to the cloud provider managing the servers and capacity planning. What you will learn Discover what microservices offer above and beyond other architectures Create a serverless application with AWS Gain secure access to data and resources Run tests on your configuration and code Create a highly available serverless microservice data API Build, deploy, and run your serverless configuration and code Who this book is for If you are a developer with basic knowledge of Python and want to learn how to build, test, deploy, and secure microservices, then this book is for you. No prior knowledge of building microservices is required.
    Note: Description based on online resource; title from title page (Safari, viewed May 8, 2019)
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  • 31
    ISBN: 9781789533446 , 1789533449
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: TensorFlow ; Reinforcement learning ; Neural networks (Computer science) ; Python (Computer program language) ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Leverage the power of Tensorflow to Create powerful software agents that can self-learn to perform real-world tasks Key Features Explore efficient Reinforcement Learning algorithms and code them using TensorFlow and Python Train Reinforcement Learning agents for problems, ranging from computer games to autonomous driving. Formulate and devise selective algorithms and techniques in your applications in no time. Book Description Advances in reinforcement learning algorithms have made it possible to use them for optimal control in several different industrial applications. With this book, you will apply Reinforcement Learning to a range of problems, from computer games to autonomous driving. The book starts by introducing you to essential Reinforcement Learning concepts such as agents, environments, rewards, and advantage functions. You will also master the distinctions between on-policy and off-policy algorithms, as well as model-free and model-based algorithms. You will also learn about several Reinforcement Learning algorithms, such as SARSA, Deep Q-Networks (DQN), Deep Deterministic Policy Gradients (DDPG), Asynchronous Advantage Actor-Critic (A3C), Trust Region Policy Optimization (TRPO), and Proximal Policy Optimization (PPO). The book will also show you how to code these algorithms in TensorFlow and Python and apply them to solve computer games from OpenAI Gym. Finally, you will also learn how to train a car to drive autonomously in the Torcs racing car simulator. By the end of the book, you will be able to design, build, train, and evaluate feed-forward neural networks and convolutional neural networks. You will also have mastered coding state-of-the-art algorithms and also training agents for various control problems. What you will learn Understand the theory and concepts behind modern Reinforcement Learning algorithms Code state-of-the-art Reinforcement Learning algorithms with discrete or continuous actions Develop Reinforcement Learning algorithms and apply them to training agents to play computer games Explore DQN, DDQN, and Dueling architectures to play Atari's Breakout using TensorFlow Use A3C to play CartPole and LunarLander Train an agent to drive a car autonomously in a simulator Who this book is for Data scientists and AI developers who wish to quickly get started with training effective reinforcement learning models in TensorFlow will find this book very useful. Prior knowledge of machine learning and deep learning concepts (...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed May 14, 2019)
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  • 32
    ISBN: 9781789133318 , 1789133319
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Neural networks (Computer science) ; Machine learning ; Artificial intelligence ; Electronic books ; local ; Electronic books
    Abstract: Build your Machine Learning portfolio by creating 6 cutting-edge Artificial Intelligence projects using neural networks in Python Key Features Discover neural network architectures (like CNN and LSTM) that are driving recent advancements in AI Build expert neural networks in Python using popular libraries such as Keras Includes projects such as object detection, face identification, sentiment analysis, and more Book Description Neural networks are at the core of recent AI advances, providing some of the best resolutions to many real-world problems, including image recognition, medical diagnosis, text analysis, and more. This book goes through some basic neural network and deep learning concepts, as well as some popular libraries in Python for implementing them. It contains practical demonstrations of neural networks in domains such as fare prediction, image classification, sentiment analysis, and more. In each case, the book provides a problem statement, the specific neural network architecture required to tackle that problem, the reasoning behind the algorithm used, and the associated Python code to implement the solution from scratch. In the process, you will gain hands-on experience with using popular Python libraries such as Keras to build and train your own neural networks from scratch. By the end of this book, you will have mastered the different neural network architectures and created cutting-edge AI projects in Python that will immediately strengthen your machine learning portfolio. What you will learn Learn various neural network architectures and its advancements in AI Master deep learning in Python by building and training neural network Master neural networks for regression and classification Discover convolutional neural networks for image recognition Learn sentiment analysis on textual data using Long Short-Term Memory Build and train a highly accurate facial recognition security system Who this book is for This book is a perfect match for data scientists, machine learning engineers, and deep learning enthusiasts who wish to create practical neural network projects in Python. Readers should already have some basic knowledge of machine learning and neural networks.
    Note: Description based on online resource; title from title page (Safari, viewed April 18, 2019)
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  • 33
    ISBN: 9781789134261 , 1789134269
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Application software ; Development ; Information technology ; Management ; Electronic books ; Electronic books ; local
    Abstract: Leverage the features and libraries of Python to administrate your environment efficiently. Key Features Learn how to solve problems of system administrators and automate routine activities Learn to handle regular expressions, network administration Building GUI, web-scraping and database administration including data analytics Book Description Python has evolved over time and extended its features in relation to every possible IT operation. Python is simple to learn, yet has powerful libraries that can be used to build powerful Python scripts for solving real-world problems and automating administrators' routine activities. The objective of this book is to walk through a series of projects that will teach readers Python scripting with each project. This book will initially cover Python installation and quickly revise basic to advanced programming fundamentals. The book will then focus on the development process as a whole, from setup to planning to building different tools. It will include IT administrators' routine activities (text processing, regular expressions, file archiving, and encryption), network administration (socket programming, email handling, the remote controlling of devices using telnet/ssh, and protocols such as SNMP/DHCP), building graphical user interface, working with websites (Apache log file processing, SOAP and REST APIs communication, and web scraping), and database administration (MySQL and similar database data administration, data analytics, and reporting). By the end of this book, you will be able to use the latest features of Python and be able to build powerful tools that will solve challenging, real-world tasks What you will learn Understand how to install Python and debug Python scripts Understand and write scripts for automating testing and routine administrative activities Understand how to write scripts for text processing, encryption, decryption, and archiving Handle files, such as pdf, excel, csv, and txt files, and generate reports Write scripts for remote network administration, including handling emails Build interactive tools using a graphical user interface Handle Apache log files, SOAP and REST APIs communication Automate database administration and perform statistical analysis Who this book is for This book would be ideal for users with some basic understanding of Python programming and who are interested in scaling their programming skills to command line scripting and system administration. Prior ...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 25, 2019)
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  • 34
    ISBN: 9781789800753 , 1789800757
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Python (Computer program language) ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Discover powerful ways to effectively solve real-world machine learning problems using key libraries including scikit-learn, TensorFlow, and PyTorch Key Features Learn and implement machine learning algorithms in a variety of real-life scenarios Cover a range of tasks catering to supervised, unsupervised and reinforcement learning techniques Find easy-to-follow code solutions for tackling common and not-so-common challenges Book Description This eagerly anticipated second edition of the popular Python Machine Learning Cookbook will enable you to adopt a fresh approach to dealing with real-world machine learning and deep learning tasks. With the help of over 100 recipes, you will learn to build powerful machine learning applications using modern libraries from the Python ecosystem. The book will also guide you on how to implement various machine learning algorithms for classification, clustering, and recommendation engines, using a recipe-based approach. With emphasis on practical solutions, dedicated sections in the book will help you to apply supervised and unsupervised learning techniques to real-world problems. Toward the concluding chapters, you will get to grips with recipes that teach you advanced techniques including reinforcement learning, deep neural networks, and automated machine learning. By the end of this book, you will be equipped with the skills you need to apply machine learning techniques and leverage the full capabilities of the Python ecosystem through real-world examples. What you will learn Use predictive modeling and apply it to real-world problems Explore data visualization techniques to interact with your data Learn how to build a recommendation engine Understand how to interact with text data and build models to analyze it Work with speech data and recognize spoken words using Hidden Markov Models Get well versed with reinforcement learning, automated ML, and transfer learning Work with image data and build systems for image recognition and biometric face recognition Use deep neural networks to build an optical character recognition system Who this book is for This book is for data scientists, machine learning developers, deep learning enthusiasts and Python programmers who want to solve real-world challenges using machine-learning techniques and algorithms. If you are facing challenges at work and want ready-to-use code solutions to cover key tasks in machine learning and the deep learning domain, then this book is w...
    Note: Previous edition published: 2016. - Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed May 15, 2019)
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  • 35
    ISBN: 9781788624640 , 1788624645
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Blockchains (Databases) ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: Implement real-world decentralized applications using Python, Vyper, Populus, and Ethereum Key Features Stay up-to-date with everything you need to know about the blockchain ecosystem Implement smart contracts, wallets, and decentralized applications(DApps) using Python libraries Get deeper insights into storing content in a distributed storage platform Book Description Blockchain is seen as the main technological solution that works as a public ledger for all cryptocurrency transactions. This book serves as a practical guide to developing a full-fledged decentralized application with Python to interact with the various building blocks of blockchain applications. Hands-On Blockchain for Python Developers starts by demonstrating how blockchain technology and cryptocurrency hashing works. You will understand the fundamentals and benefits of smart contracts such as censorship resistance and transaction accuracy. As you steadily progress, you'll go on to build smart contracts using Vyper, which has a similar syntax to Python. This experience will further help you unravel the other benefits of smart contracts, including reliable storage and backup, and efficiency. You'll also use web3.py to interact with smart contracts and leverage the power of both the web3.py and Populus framework to build decentralized applications that offer security and seamless integration with cryptocurrencies. As you explore later chapters, you'll learn how to create your own token on top of Ethereum and build a cryptocurrency wallet graphical user interface (GUI) that can handle Ethereum and Ethereum Request for Comments (ERC-20) tokens using the PySide2 library. This will enable users to seamlessly store, send, and receive digital money. Toward the end, you'll implement InterPlanetary File System (IPFS) technology in your decentralized application to provide a peer-to-peer filesystem that can store and expose media. By the end of this book, you'll be well-versed in blockchain programming and be able to build end-to-end decentralized applications on a range of domains using Python. What you will learn Understand blockchain technology and what makes it an immutable database Use the features of web3.py API to interact with the smart contract Create your own cryptocurrency and token in Ethereum using Vyper Use IPFS features to store content on the decentralized storage platform Implement a Twitter-like decentralized application with a desktop frontend Build decentralized app...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 28, 2019)
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  • 36
    ISBN: 9781789349276 , 1789349273
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Artificial intelligence ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Discover the skill-sets required to implement various approaches to Machine Learning with Python Key Features Explore unsupervised learning with clustering, autoencoders, restricted Boltzmann machines, and more Build your own neural network models using modern Python libraries Practical examples show you how to implement different machine learning and deep learning techniques Book Description Unsupervised learning is about making use of raw, untagged data and applying learning algorithms to it to help a machine predict its outcome. With this book, you will explore the concept of unsupervised learning to cluster large sets of data and analyze them repeatedly until the desired outcome is found using Python. This book starts with the key differences between supervised, unsupervised, and semi-supervised learning. You will be introduced to the best-used libraries and frameworks from the Python ecosystem and address unsupervised learning in both the machine learning and deep learning domains. You will explore various algorithms, techniques that are used to implement unsupervised learning in real-world use cases. You will learn a variety of unsupervised learning approaches, including randomized optimization, clustering, feature selection and transformation, and information theory. You will get hands-on experience with how neural networks can be employed in unsupervised scenarios. You will also explore the steps involved in building and training a GAN in order to process images. By the end of this book, you will have learned the art of unsupervised learning for different real-world challenges. What you will learn Use cluster algorithms to identify and optimize natural groups of data Explore advanced non-linear and hierarchical clustering in action Soft label assignments for fuzzy c-means and Gaussian mixture models Detect anomalies through density estimation Perform principal component analysis using neural network models Create unsupervised models using GANs Who this book is for This book is intended for statisticians, data scientists, machine learning developers, and deep learning practitioners who want to build smart applications by implementing key building block unsupervised learning, and master all the new techniques and algorithms offered in machine learning and deep learning using real-world examples. Some prior knowledge of machine learning concepts and statistics is desirable.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed April 18, 2019)
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  • 37
    ISBN: 9781789132502 , 1789132509
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Implement machine learning algorithms to build ensemble models using Keras, H2O, Scikit-Learn, Pandas and more Key Features Apply popular machine learning algorithms using a recipe-based approach Implement boosting, bagging, and stacking ensemble methods to improve machine learning models Discover real-world ensemble applications and encounter complex challenges in Kaggle competitions Book Description Ensemble modeling is an approach used to improve the performance of machine learning models. It combines two or more similar or dissimilar machine learning algorithms to deliver superior intellectual powers. This book will help you to implement popular machine learning algorithms to cover different paradigms of ensemble machine learning such as boosting, bagging, and stacking. The Ensemble Machine Learning Cookbook will start by getting you acquainted with the basics of ensemble techniques and exploratory data analysis. You'll then learn to implement tasks related to statistical and machine learning algorithms to understand the ensemble of multiple heterogeneous algorithms. It will also ensure that you don't miss out on key topics, such as like resampling methods. As you progress, you'll get a better understanding of bagging, boosting, stacking, and working with the Random Forest algorithm using real-world examples. The book will highlight how these ensemble methods use multiple models to improve machine learning results, as compared to a single model. In the concluding chapters, you'll delve into advanced ensemble models using neural networks, natural language processing, and more. You'll also be able to implement models such as fraud detection, text categorization, and sentiment analysis. By the end of this book, you'll be able to harness ensemble techniques and the working mechanisms of machine learning algorithms to build intelligent models using individual recipes. What you will learn Understand how to use machine learning algorithms for regression and classification problems Implement ensemble techniques such as averaging, weighted averaging, and max-voting Get to grips with advanced ensemble methods, such as bootstrapping, bagging, and stacking Use Random Forest for tasks such as classification and regression Implement an ensemble of homogeneous and heterogeneous machine learning algorithms Learn and implement various boosting techniques, such as AdaBoost, Gradient Boosting Machine, and XGBoost Who this book is for This book is designed fo...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 25, 2019)
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  • 38
    Online Resource
    Online Resource
    Birmingham, UK : Packt Publishing
    ISBN: 9781789955989 , 178995598X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Natural language processing (Computer science) ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Use Python and NLTK (Natural Language Toolkit) to build out your own text classifiers and solve common NLP problems. Key Features Assimilate key NLP concepts and terminologies Explore popular NLP tools and techniques Gain practical experience using NLP in application code Book Description If NLP hasn't been your forte, Natural Language Processing Fundamentals will make sure you set off to a steady start. This comprehensive guide will show you how to effectively use Python libraries and NLP concepts to solve various problems. You'll be introduced to natural language processing and its applications through examples and exercises. This will be followed by an introduction to the initial stages of solving a problem, which includes problem definition, getting text data, and preparing it for modeling. With exposure to concepts like advanced natural language processing algorithms and visualization techniques, you'll learn how to create applications that can extract information from unstructured data and present it as impactful visuals. Although you will continue to learn NLP-based techniques, the focus will gradually shift to developing useful applications. In these sections, you'll understand how to apply NLP techniques to answer questions as can be used in chatbots. By the end of this book, you'll be able to accomplish a varied range of assignments ranging from identifying the most suitable type of NLP task for solving a problem to using a tool like spacy or gensim for performing sentiment analysis. The book will easily equip you with the knowledge you need to build applications that interpret human language. What you will learn Obtain, verify, and clean data before transforming it into a correct format for use Perform data analysis and machine learning tasks using Python Understand the basics of computational linguistics Build models for general natural language processing tasks Evaluate the performance of a model with the right metrics Visualize, quantify, and perform exploratory analysis from any text data Who this book is for Natural Language Processing Fundamentals is designed for novice and mid-level data scientists and machine learning developers who want to gather and analyze text data to build an NLP-powered product. It'll help you to have prior experience of coding in Python using data types, writing functions, and importing libraries. Some experience with linguistics and probability is useful but not necessary.
    Note: Description based on online resource; title from cover (Safari, viewed May 15, 2019)
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  • 39
    ISBN: 9781788994866 , 1788994868
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Artificial intelligence ; Machine learning ; Neural networks (Computer science) ; Electronic books ; Electronic books ; local
    Abstract: Implement machine learning and deep learning methodologies to build smart, cognitive AI projects using Python Key Features A go-to guide to help you master AI algorithms and concepts 8 real-world projects tackling different challenges in healthcare, e-commerce, and surveillance Use TensorFlow, Keras, and other Python libraries to implement smart AI applications Book Description This book will be a perfect companion if you want to build insightful projects from leading AI domains using Python. The book covers detailed implementation of projects from all the core disciplines of AI. We start by covering the basics of how to create smart systems using machine learning and deep learning techniques. You will assimilate various neural network architectures such as CNN, RNN, LSTM, to solve critical new world challenges. You will learn to train a model to detect diabetic retinopathy conditions in the human eye and create an intelligent system for performing a video-to-text translation. You will use the transfer learning technique in the healthcare domain and implement style transfer using GANs. Later you will learn to build AI-based recommendation systems, a mobile app for sentiment analysis and a powerful chatbot for carrying customer services. You will implement AI techniques in the cybersecurity domain to generate Captchas. Later you will train and build autonomous vehicles to self-drive using reinforcement learning. You will be using libraries from the Python ecosystem such as TensorFlow, Keras and more to bring the core aspects of machine learning, deep learning, and AI. By the end of this book, you will be skilled to build your own smart models for tackling any kind of AI problems without any hassle. What you will learn Build an intelligent machine translation system using seq-2-seq neural translation machines Create AI applications using GAN and deploy smart mobile apps using TensorFlow Translate videos into text using CNN and RNN Implement smart AI Chatbots, and integrate and extend them in several domains Create smart reinforcement, learning-based applications using Q-Learning Break and generate CAPTCHA using Deep Learning and Adversarial Learning Who this book is for This book is intended for data scientists, machine learning professionals, and deep learning practitioners who are ready to extend their knowledge and potential in AI. If you want to build real-life smart systems to play a crucial role in every complex domain, then this book is w...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 25, 2019)
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  • 40
    ISBN: 9781789138191 , 1789138191
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Blockchains (Databases) ; Application software ; Development ; Cryptocurrencies ; Bitcoin ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Learn the foundations of blockchain technology - its core concepts and algorithmic solutions across cryptography, peer-to-peer technology, and game theory. Key Features Learn the core concepts and foundations of the blockchain and cryptocurrencies Understand the protocols and algorithms behind decentralized applications Master how to architect, build, and optimize blockchain applications Book Description Blockchain technology is a combination of three popular concepts: cryptography, peer-to-peer networking, and game theory. This book is for anyone who wants to dive into blockchain from first principles and learn how decentralized applications and cryptocurrencies really work. This book begins with an overview of blockchain technology, including key definitions, its purposes and characteristics, so you can assess the full potential of blockchain. All essential aspects of cryptography are then presented, as the backbone of blockchain. For readers who want to study the underlying algorithms of blockchain, you'll see Python implementations throughout. You'll then learn how blockchain architecture can create decentralized applications. You'll see how blockchain achieves decentralization through peer-to-peer networking, and how a simple blockchain can be built in a P2P network. You'll learn how these elements can implement a cryptocurrency such as Bitcoin, and the wider applications of blockchain work through smart contracts. Blockchain optimization techniques, and blockchain security strategies are then presented. To complete this foundation, we consider blockchain applications in the financial and non-financial sectors, and also analyze the future of blockchain. A study of blockchain use cases includes supply chains, payment systems, crowdfunding, and DAOs, which rounds out your foundation in blockchain technology. What you will learn The core concepts and technical foundations of blockchain The algorithmic principles and solutions that make up blockchain and cryptocurrencies Blockchain cryptography explained in detail How to realize blockchain projects with hands-on Python code How to architect the blockchain and blockchain applications Decentralized application development with MultiChain, NEO, and Ethereum Optimizing and enhancing blockchain performance and security Classical blockchain use cases and how to implement them Who this book is for This book is for anyone who wants to dive into blockchain technology from first principles and build a ...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 14, 2019)
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  • 41
    ISBN: 9781788830232 , 1788830237
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Computer networks ; Management ; Client/server computing ; Electronic books ; Electronic books ; local
    Abstract: Power up your network applications with Python programming Key Features Master Python skills to develop powerful network applications Grasp the fundamentals and functionalities of SDN Design multi-threaded, event-driven architectures for echo and chat servers Book Description This Learning Path highlights major aspects of Python network programming such as writing simple networking clients, creating and deploying SDN and NFV systems, and extending your network with Mininet. You'll also learn how to automate legacy and the latest network devices. As you progress through the chapters, you'll use Python for DevOps and open source tools to test, secure, and analyze your network. Toward the end, you'll develop client-side applications, such as web API clients, email clients, SSH, and FTP, using socket programming. By the end of this Learning Path, you will have learned how to analyze a network's security vulnerabilities using advanced network packet capture and analysis techniques. This Learning Path includes content from the following Packt products: Practical Network Automation by Abhishek Ratan Mastering Python Networking by Eric Chou Python Network Programming Cookbook, Second Edition by Pradeeban Kathiravelu, Dr. M. O. Faruque Sarker What you will learn Create socket-based networks with asynchronous models Develop client apps for web APIs, including S3 Amazon and Twitter Talk to email and remote network servers with different protocols Integrate Python with Cisco, Juniper, and Arista eAPI for automation Use Telnet and SSH connections for remote system monitoring Interact with websites via XML-RPC, SOAP, and REST APIs Build networks with Ryu, OpenDaylight, Floodlight, ONOS, and POX Configure virtual networks in different deployment environments Who this book is for If you are a Python developer or a system administrator who wants to start network programming, this Learning Path gets you a step closer to your goal. IT professionals and DevOps engineers who are new to managing network devices or those with minimal experience looking to expand their knowledge and skills in Python will also find this Learning Path useful. Although prior knowledge of networking is not required, some experience in Python programming will be helpful for a better understanding of the concepts in the Learning Path.
    Note: Description based on online resource; title from title page (Safari, viewed March 19, 2019)
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  • 42
    ISBN: 9781789616279 , 1789616271
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Machine learning ; Python (Computer program language) ; Watson (Computer) ; Computer algorithms ; Electronic books ; Electronic books ; local
    Abstract: Learn how to build complete machine learning systems with IBM Cloud and Watson Machine learning services Key Features Implement data science and machine learning techniques to draw insights from real-world data Understand what IBM Cloud platform can help you to implement cognitive insights within applications Understand the role of data representation and feature extraction in any machine learning system Book Description IBM Cloud is a collection of cloud computing services for data analytics using machine learning and artificial intelligence (AI). This book is a complete guide to help you become well versed with machine learning on the IBM Cloud using Python. Hands-On Machine Learning with IBM Watson starts with supervised and unsupervised machine learning concepts, in addition to providing you with an overview of IBM Cloud and Watson Machine Learning. You'll gain insights into running various techniques, such as K-means clustering, K-nearest neighbor (KNN), and time series prediction in IBM Cloud with real-world examples. The book will then help you delve into creating a Spark pipeline in Watson Studio. You will also be guided through deep learning and neural network principles on the IBM Cloud using TensorFlow. With the help of NLP techniques, you can then brush up on building a chatbot. In later chapters, you will cover three powerful case studies, including the facial expression classification platform, the automated classification of lithofacies, and the multi-biometric identity authentication platform, helping you to become well versed with these methodologies. By the end of this book, you will be ready to build efficient machine learning solutions on the IBM Cloud and draw insights from the data at hand using real-world examples. What you will learn Understand key characteristics of IBM machine learning services Run supervised and unsupervised techniques in the cloud Understand how to create a Spark pipeline in Watson Studio Implement deep learning and neural networks on the IBM Cloud with TensorFlow Create a complete, cloud-based facial expression classification solution Use biometric traits to build a cloud-based human identification system Who this book is for This beginner-level book is for data scientists and machine learning engineers who want to get started with IBM Cloud and its machine learning services using practical examples. Basic knowledge of Python and some understanding of machine learning will be useful.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed May 8, 2019)
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  • 43
    ISBN: 9781788997775 , 1788997778
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Machine learning ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Discover a project-based approach to mastering machine learning concepts by applying them to everyday problems using libraries such as scikit-learn, TensorFlow, and Keras Key Features Get to grips with Python's machine learning libraries including scikit-learn, TensorFlow, and Keras Implement advanced concepts and popular machine learning algorithms in real-world projects Build analytics, computer vision, and neural network projects Book Description Machine learning is transforming the way we understand and interact with the world around us. This book is the perfect guide for you to put your knowledge and skills into practice and use the Python ecosystem to cover key domains in machine learning. This second edition covers a range of libraries from the Python ecosystem, including TensorFlow and Keras, to help you implement real-world machine learning projects. The book begins by giving you an overview of machine learning with Python. With the help of complex datasets and optimized techniques, you'll go on to understand how to apply advanced concepts and popular machine learning algorithms to real-world projects. Next, you'll cover projects from domains such as predictive analytics to analyze the stock market and recommendation systems for GitHub repositories. In addition to this, you'll also work on projects from the NLP domain to create a custom news feed using frameworks such as scikit-learn, TensorFlow, and Keras. Following this, you'll learn how to build an advanced chatbot, and scale things up using PySpark. In the concluding chapters, you can look forward to exciting insights into deep learning and you'll even create an application using computer vision and neural networks. By the end of this book, you'll be able to analyze data seamlessly and make a powerful impact through your projects. What you will learn Understand the Python data science stack and commonly used algorithms Build a model to forecast the performance of an Initial Public Offering (IPO) over an initial discrete trading window Understand NLP concepts by creating a custom news feed Create applications that will recommend GitHub repositories based on ones you've starred, watched, or forked Gain the skills to build a chatbot from scratch using PySpark Develop a market-prediction app using stock data Delve into advanced concepts such as computer vision, neural networks, and deep learning Who this book is for This book is for machine learning practitioners, data scientists, and...
    Note: Previous edition published: 2016. - Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 25, 2019)
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  • 44
    ISBN: 9781788999465 , 1788999460
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Penetration testing (Computer security) ; Electronic books ; Electronic books ; local
    Abstract: Implement defensive techniques in your ecosystem successfully with Python Key Features Identify and expose vulnerabilities in your infrastructure with Python Learn custom exploit development . Make robust and powerful cybersecurity tools with Python Book Description With the current technological and infrastructural shift, penetration testing is no longer a process-oriented activity. Modern-day penetration testing demands lots of automation and innovation; the only language that dominates all its peers is Python. Given the huge number of tools written in Python, and its popularity in the penetration testing space, this language has always been the first choice for penetration testers. Hands-On Penetration Testing with Python walks you through advanced Python programming constructs. Once you are familiar with the core concepts, you'll explore the advanced uses of Python in the domain of penetration testing and optimization. You'll then move on to understanding how Python, data science, and the cybersecurity ecosystem communicate with one another. In the concluding chapters, you'll study exploit development, reverse engineering, and cybersecurity use cases that can be automated with Python. By the end of this book, you'll have acquired adequate skills to leverage Python as a helpful tool to pentest and secure infrastructure, while also creating your own custom exploits. What you will learn Get to grips with Custom vulnerability scanner development Familiarize yourself with web application scanning automation and exploit development Walk through day-to-day cybersecurity scenarios that can be automated with Python Discover enterprise-or organization-specific use cases and threat-hunting automation Understand reverse engineering, fuzzing, buffer overflows , key-logger development, and exploit development for buffer overflows. Understand web scraping in Python and use it for processing web responses Explore Security Operations Centre (SOC) use cases Get to understand Data Science, Python, and cybersecurity all under one hood Who this book is for If you are a security consultant , developer or a cyber security enthusiast with little or no knowledge of Python and want in-depth insight into how the pen-testing ecosystem and python combine to create offensive tools , exploits , automate cyber security use-cases and much more then this book is for you. Hands-On Penetration Testing with Python guides you through the advanced uses of Python for cybersecu...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed February 15, 2019)
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  • 45
    ISBN: 9781838553692 , 183855369X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Series Statement: Learning path
    Keywords: Python (Computer program language) ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: Create distributed applications with clever design patterns to solve complex problems Key Features Set up and run distributed algorithms on a cluster using Dask and PySpark Master skills to accurately implement concurrency in your code Gain practical experience of Python design patterns with real-world examples Book Description This Learning Path shows you how to leverage the power of both native and third-party Python libraries for building robust and responsive applications. You will learn about profilers and reactive programming, concurrency and parallelism, as well as tools for making your apps quick and efficient. You will discover how to write code for parallel architectures using TensorFlow and Theano, and use a cluster of computers for large-scale computations using technologies such as Dask and PySpark. With the knowledge of how Python design patterns work, you will be able to clone objects, secure interfaces, dynamically choose algorithms, and accomplish much more in high performance computing. By the end of this Learning Path, you will have the skills and confidence to build engaging models that quickly offer efficient solutions to your problems. This Learning Path includes content from the following Packt products: ? Python High Performance - Second Edition by Gabriele Lanaro ? Mastering Concurrency in Python by Quan Nguyen ? Mastering Python Design Patterns by Sakis Kasampalis What you will learn Use NumPy and pandas to import and manipulate datasets Achieve native performance with Cython and Numba Write asynchronous code using asyncio and RxPy Design highly scalable programs with application scaffolding Explore abstract methods to maintain data consistency Clone objects using the prototype pattern Use the adapter pattern to make incompatible interfaces compatible Employ the strategy pattern to dynamically choose an algorithm Who this book is for This Learning Path is specially designed for Python developers who want to build high-performance applications and learn about single core and multi-core programming, distributed concurrency, and Python design patterns. Some experience with Python programming language will help you get the most out of this Learning Path.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed April 22, 2019)
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  • 46
    ISBN: 9781838553333 , 1838553339
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Series Statement: Learning path
    Keywords: Python (Computer program language) ; Internet of things ; Raspberry Pi (Computer) ; Machine-to-machine communications ; Electronic books ; Electronic books ; local
    Abstract: Build clever, collaborative, and powerful automation systems with the Raspberry Pi and Python. Key Features Create your own Pi-Rover or Pi-Hexipod robots Develop practical applications in Python using Raspberry Pi Build your own Jarvis, a highly advanced computerized AI Book Description This Learning Path takes you on a journey in the world of robotics and teaches you all that you can achieve with Raspberry Pi and Python. It teaches you to harness the power of Python with the Raspberry Pi 3 and the Raspberry Pi zero to build superlative automation systems that can transform your business. You will learn to create text classifiers, predict sentiment in words, and develop applications with the Tkinter library. Things will get more interesting when you build a human face detection and recognition system and a home automation system in Python, where different appliances are controlled using the Raspberry Pi. With such diverse robotics projects, you'll grasp the basics of robotics and its functions, and understand the integration of robotics with the IoT environment. By the end of this Learning Path, you will have covered everything from configuring a robotic controller, to creating a self-driven robotic vehicle using Python. Raspberry Pi 3 Cookbook for Python Programmers - Third Edition by Tim Cox, Dr. Steven Lawrence Fernandes Python Programming with Raspberry Pi by Sai Yamanoor, Srihari Yamanoor Python Robotics Projects by Prof. Diwakar Vaish What you will learn Build text classifiers and predict sentiment in words with the Tkinter library Develop human face detection and recognition systems Create a neural network module for optical character recognition Build a mobile robot using the Raspberry Pi as a controller Understand how to interface sensors, actuators, and LED displays work Apply machine learning techniques to your models Interface your robots with Bluetooth Who this book is for This Learning Path is specially designed for Python developers who want to take their skills to the next level by creating robots that can enhance people's lives. Familiarity with Python and electronics will aid understanding the concepts in this Learning Path.
    Note: Description based on online resource; title from title page (Safari, viewed April 5, 2019)
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  • 47
    ISBN: 9781788994873 , 1788994876
    Language: English
    Pages: 1 online resource (1 volume) , illustrations, maps
    Edition: Third edition.
    Keywords: Geographic information systems ; Computer programs ; Geodatabases ; Computer programs ; Cartography ; Computer programs ; Geospatial data ; Data processing ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Go beyond the basics and unleash the full power of QGIS 3.4 and 3.6 with practical, step-by-step examples Key Features One-stop solution to all of your GIS needs Master QGIS by learning about database integration, and geoprocessing tools Learn about the new and updated Processing toolbox and perform spatial analysis Book Description QGIS is an open source solution to GIS and widely used by GIS professionals all over the world. It is the leading alternative to proprietary GIS software. Although QGIS is described as intuitive, it is also, by default, complex. Knowing which tools to use and how to apply them is essential to producing valuable deliverables on time. Starting with a refresher on the QGIS basics and getting you acquainted with the latest QGIS 3.6 updates, this book will take you all the way through to teaching you how to create a spatial database and a GeoPackage. Next, you will learn how to style raster and vector data by choosing and managing different colors. The book will then focus on processing raster and vector data. You will be then taught advanced applications, such as creating and editing vector data. Along with that, you will also learn about the newly updated Processing Toolbox, which will help you develop the advanced data visualizations. The book will then explain to you the graphic modeler, how to create QGIS plugins with PyQGIS, and how to integrate Python analysis scripts with QGIS. By the end of the book, you will understand how to work with all aspects of QGIS and will be ready to use it for any type of GIS work. What you will learn Create and manage a spatial database Get to know advanced techniques to style GIS data Prepare both vector and raster data for processing Add heat maps, live layer effects, and labels to your maps Master LAStools and GRASS integration with the Processing Toolbox Edit and repair topological data errors Automate workflows with batch processing and the QGIS Graphical Modeler Integrate Python scripting into your data processing workflows Develop your own QGIS plugins Who this book is for If you are a GIS professional, a consultant, a student, or perhaps a fast learner who wants to go beyond the basics of QGIS, then this book is for you. It will prepare you to realize the full potential of QGIS.
    Note: Previous edition published: 2016. - Description based on online resource; title from title page (Safari, viewed May 1, 2019)
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  • 48
    ISBN: 9781789952100 , 1789952107
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Marketing ; Data processing ; Marketing research ; Python (Computer program language) ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Explore new and more sophisticated tools that reduce your marketing analytics efforts and give you precise results Key Features Study new techniques for marketing analytics Explore uses of machine learning to power your marketing analyses Work through each stage of data analytics with the help of multiple examples and exercises Book Description Data Science for Marketing Analytics covers every stage of data analytics, from working with a raw dataset to segmenting a population and modeling different parts of the population based on the segments. The book starts by teaching you how to use Python libraries, such as pandas and Matplotlib, to read data from Python, manipulate it, and create plots, using both categorical and continuous variables. Then, you'll learn how to segment a population into groups and use different clustering techniques to evaluate customer segmentation. As you make your way through the chapters, you'll explore ways to evaluate and select the best segmentation approach, and go on to create a linear regression model on customer value data to predict lifetime value. In the concluding chapters, you'll gain an understanding of regression techniques and tools for evaluating regression models, and explore ways to predict customer choice using classification algorithms. Finally, you'll apply these techniques to create a churn model for modeling customer product choices. By the end of this book, you will be able to build your own marketing reporting and interactive dashboard solutions. What you will learn Analyze and visualize data in Python using pandas and Matplotlib Study clustering techniques, such as hierarchical and k-means clustering Create customer segments based on manipulated data Predict customer lifetime value using linear regression Use classification algorithms to understand customer choice Optimize classification algorithms to extract maximal information Who this book is for Data Science for Marketing Analytics is designed for developers and marketing analysts looking to use new, more sophisticated tools in their marketing analytics efforts. It'll help if you have prior experience of coding in Python and knowledge of high school level mathematics. Some experience with databases, Excel, statistics, or Tableau is useful but not necessary.
    Note: Includes bibliographical references. - Description based on online resource; title from copyright page (Safari, viewed May 15, 2019)
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  • 49
    ISBN: 9781838559984 , 1838559981
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Series Statement: Learning path
    Keywords: Python (Computer program language) ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: Harness the power of Python objects and data structures to implement algorithms for analyzing your data and efficiently extracting information Key Features Turn your designs into working software by learning the Python syntax Write robust code with a solid understanding of Python data structures Understand when to use the functional or the OOP approach Book Description This Learning Path helps you get comfortable with the world of Python. It starts with a thorough and practical introduction to Python. You'll quickly start writing programs, building websites, and working with data by harnessing Python's renowned data science libraries. With the power of linked lists, binary searches, and sorting algorithms, you'll easily create complex data structures, such as graphs, stacks, and queues. After understanding cooperative inheritance, you'll expertly raise, handle, and manipulate exceptions. You will effortlessly integrate the object-oriented and not-so-object-oriented aspects of Python, and create maintainable applications using higher level design patterns. Once you've covered core topics, you'll understand the joy of unit testing and just how easy it is to create unit tests. By the end of this Learning Path, you will have built components that are easy to understand, debug, and can be used across different applications. This Learning Path includes content from the following Packt products: Learn Python Programming - Second Edition by Fabrizio Romano Python Data Structures and Algorithms by Benjamin Baka Python 3 Object-Oriented Programming by Dusty Phillips What you will learn Use data structures and control flow to write code Use functions to bundle together a sequence of instructions Implement objects in Python by creating classes and defining methods Design public interfaces using abstraction, encapsulation and information hiding Raise, define, and manipulate exceptions using special error objects Create bulletproof and reliable software by writing unit tests Learn the common programming patterns and algorithms used in Python Who this book is for If you are relatively new to coding and want to write scripts or programs to accomplish tasks using Python, or if you are an object-oriented programmer for other languages and seeking a leg up in the world of Python, then this Learning Path is for you. Though not essential, it will help you to have basic knowledge of programming and OOP.
    Note: Description based on online resource; title from title page (Safari, viewed April 24, 2019)
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  • 50
    ISBN: 9781789348828 , 178934882X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Marketing ; Data processing ; Machine learning ; Marketing research ; Python (Computer program language) ; R (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Optimize your marketing strategies through analytics and machine learning Key Features Understand how data science drives successful marketing campaigns Use machine learning for better customer engagement, retention, and product recommendations Extract insights from your data to optimize marketing strategies and increase profitability Book Description Regardless of company size, the adoption of data science and machine learning for marketing has been rising in the industry. With this book, you will learn to implement data science techniques to understand the drivers behind the successes and failures of marketing campaigns. This book is a comprehensive guide to help you understand and predict customer behaviors and create more effectively targeted and personalized marketing strategies. This is a practical guide to performing simple-to-advanced tasks, to extract hidden insights from the data and use them to make smart business decisions. You will understand what drives sales and increases customer engagements for your products. You will learn to implement machine learning to forecast which customers are more likely to engage with the products and have high lifetime value. This book will also show you how to use machine learning techniques to understand different customer segments and recommend the right products for each customer. Apart from learning to gain insights into consumer behavior using exploratory analysis, you will also learn the concept of A/B testing and implement it using Python and R. By the end of this book, you will be experienced enough with various data science and machine learning techniques to run and manage successful marketing campaigns for your business. What you will learn Learn how to compute and visualize marketing KPIs in Python and R Master what drives successful marketing campaigns with data science Use machine learning to predict customer engagement and lifetime value Make product recommendations that customers are most likely to buy Learn how to use A/B testing for better marketing decision making Implement machine learning to understand different customer segments Who this book is for If you are a marketing professional, data scientist, engineer, or a student keen to learn how to apply data science to marketing, this book is what you need! It will be beneficial to have some basic knowledge of either Python or R to work through the examples. This book will also be beneficial for beginners as it covers basic-to-adv...
    Note: Description based on online resource; title from title page (Safari, viewed May 1, 2019)
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  • 51
    Online Resource
    Online Resource
    Birmingham, UK : Packt Publishing
    ISBN: 9781789804249 , 1789804248
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Data mining ; Electronic data processing ; Information visualization ; Electronic books ; local ; Electronic books
    Abstract: Simplify your ETL processes with these hands-on data hygiene tips, tricks, and best practices. Key Features Focus on the basics of data wrangling Study various ways to extract the most out of your data in less time Boost your learning curve with bonus topics like random data generation and data integrity checks Book Description For data to be useful and meaningful, it must be curated and refined. Data Wrangling with Python teaches you the core ideas behind these processes and equips you with knowledge of the most popular tools and techniques in the domain. The book starts with the absolute basics of Python, focusing mainly on data structures. It then delves into the fundamental tools of data wrangling like NumPy and Pandas libraries. You'll explore useful insights into why you should stay away from traditional ways of data cleaning, as done in other languages, and take advantage of the specialized pre-built routines in Python. This combination of Python tips and tricks will also demonstrate how to use the same Python backend and extract/transform data from an array of sources including the Internet, large database vaults, and Excel financial tables. To help you prepare for more challenging scenarios, you'll cover how to handle missing or wrong data, and reformat it based on the requirements from the downstream analytics tool. The book will further help you grasp concepts through real-world examples and datasets. By the end of this book, you will be confident in using a diverse array of sources to extract, clean, transform, and format your data efficiently. What you will learn Use and manipulate complex and simple data structures Harness the full potential of DataFrames and numpy.array at run time Perform web scraping with BeautifulSoup4 and html5lib Execute advanced string search and manipulation with RegEX Handle outliers and perform data imputation with Pandas Use descriptive statistics and plotting techniques Practice data wrangling and modeling using data generation techniques Who this book is for Data Wrangling with Python is designed for developers, data analysts, and business analysts who are keen to pursue a career as a full-fledged data scientist or analytics expert. Although, this book is for beginners, prior working knowledge of Python is necessary to easily grasp the concepts covered here. It will also help to have rudimentary knowledge of relational database and SQL.
    Note: Description based on online resource; title from title page (Safari, viewed April 18, 2019)
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  • 52
    ISBN: 9781789349702 , 1789349702
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Python (Computer program language) ; Machine learning ; Neural networks (Computer science) ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Learn advanced state-of-the-art deep learning techniques and their applications using popular Python libraries Key Features Build a strong foundation in neural networks and deep learning with Python libraries Explore advanced deep learning techniques and their applications across computer vision and NLP Learn how a computer can navigate in complex environments with reinforcement learning Book Description With the surge in artificial intelligence in applications catering to both business and consumer needs, deep learning is more important than ever for meeting current and future market demands. With this book, you'll explore deep learning, and learn how to put machine learning to use in your projects. This second edition of Python Deep Learning will get you up to speed with deep learning, deep neural networks, and how to train them with high-performance algorithms and popular Python frameworks. You'll uncover different neural network architectures, such as convolutional networks, recurrent neural networks, long short-term memory (LSTM) networks, and capsule networks. You'll also learn how to solve problems in the fields of computer vision, natural language processing (NLP), and speech recognition. You'll study generative model approaches such as variational autoencoders and Generative Adversarial Networks (GANs) to generate images. As you delve into newly evolved areas of reinforcement learning, you'll gain an understanding of state-of-the-art algorithms that are the main components behind popular games Go, Atari, and Dota. By the end of the book, you will be well-versed with the theory of deep learning along with its real-world applications. What you will learn Grasp the mathematical theory behind neural networks and deep learning processes Investigate and resolve computer vision challenges using convolutional networks and capsule networks Solve generative tasks using variational autoencoders and Generative Adversarial Networks Implement complex NLP tasks using recurrent networks (LSTM and GRU) and attention models Explore reinforcement learning and understand how agents behave in a complex environment Get up to date with applications of deep learning in autonomous vehicles Who this book is for This book is for data science practitioners, machine learning engineers, and those interested in deep learning who have a basic foundation in machine learning and some Python programming experience. A background in mathematics and conceptual understandi...
    Note: Description based on online resource; title from title page (Safari, viewed February 15, 2019)
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  • 53
    ISBN: 9781789342765 , 1789342767
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Computer networks ; Security measures ; Python (Computer program language) ; Computer crimes ; Investigation ; Data recovery (Computer science) ; Electronic books ; Electronic books ; local
    Abstract: Design, develop, and deploy innovative forensic solutions using Python Key Features Discover how to develop Python scripts for effective digital forensic analysis Master the skills of parsing complex data structures with Python libraries Solve forensic challenges through the development of practical Python scripts Book Description Digital forensics plays an integral role in solving complex cybercrimes and helping organizations make sense of cybersecurity incidents. This second edition of Learning Python for Forensics illustrates how Python can be used to support these digital investigations and permits the examiner to automate the parsing of forensic artifacts to spend more time examining actionable data. The second edition of Learning Python for Forensics will illustrate how to develop Python scripts using an iterative design. Further, it demonstrates how to leverage the various built-in and community-sourced forensics scripts and libraries available for Python today. This book will help strengthen your analysis skills and efficiency as you creatively solve real-world problems through instruction-based tutorials. By the end of this book, you will build a collection of Python scripts capable of investigating an array of forensic artifacts and master the skills of extracting metadata and parsing complex data structures into actionable reports. Most importantly, you will have developed a foundation upon which to build as you continue to learn Python and enhance your efficacy as an investigator. What you will learn Learn how to develop Python scripts to solve complex forensic problems Build scripts using an iterative design Design code to accommodate present and future hurdles Leverage built-in and community-sourced libraries Understand the best practices in forensic programming Learn how to transform raw data into customized reports and visualizations Create forensic frameworks to automate analysis of multiple forensic artifacts Conduct effective and efficient investigations through programmatic processing Who this book is for If you are a forensics student, hobbyist, or professional seeking to increase your understanding in forensics through the use of a programming language, then Learning Python for Forensics is for you. You are not required to have previous experience in programming to learn and master the content within this book. This material, created by forensic professionals, was written with a unique perspective and understanding for ex...
    Note: Previous edition published: 2016. - Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 25, 2019)
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  • 54
    ISBN: 9781138690332
    Language: English
    Pages: xi, 201 Seiten , 24 cm
    Series Statement: Routledge studies in human geography
    DDC: 304.80941
    Keywords: Auswanderung ; Großbritannien ; Aufsatzsammlung ; Aufsatzsammlung ; Aufsatzsammlung
    Note: Literaturangaben
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  • 55
    ISBN: 9781789349757 , 1789349753
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: OpenCV (Computer program language) ; Computer vision ; Python (Computer program language) ; Image processing ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Create advanced applications with Python and OpenCV, exploring the potential of facial recognition, machine learning, deep learning, web computing and augmented reality. Key Features Develop your computer vision skills by mastering algorithms in Open Source Computer Vision 4 (OpenCV 4)and Python Apply machine learning and deep learning techniques with TensorFlow, Keras, and PyTorch Discover the modern design patterns you should avoid when developing efficient computer vision applications Book Description OpenCV is considered to be one of the best open source computer vision and machine learning software libraries. It helps developers build complete projects in relation to image processing, motion detection, or image segmentation, among many others. OpenCV for Python enables you to run computer vision algorithms smoothly in real time, combining the best of the OpenCV C++ API and the Python language. In this book, you'll get started by setting up OpenCV and delving into the key concepts of computer vision. You'll then proceed to study more advanced concepts and discover the full potential of OpenCV. The book will also introduce you to the creation of advanced applications using Python and OpenCV, enabling you to develop applications that include facial recognition, target tracking, or augmented reality. Next, you'll learn machine learning techniques and concepts, understand how to apply them in real-world examples, and also explore their benefits, including real-time data production and faster data processing. You'll also discover how to translate the functionality provided by OpenCV into optimized application code projects using Python bindings. Toward the concluding chapters, you'll explore the application of artificial intelligence and deep learning techniques using the popular Python libraries TensorFlow, and Keras. By the end of this book, you'll be able to develop advanced computer vision applications to meet your customers' demands. What you will learn Handle files and images, and explore various image processing techniques Explore image transformations, including translation, resizing, and cropping Gain insights into building histograms Brush up on contour detection, filtering, and drawing Work with Augmented Reality to build marker-based and markerless applications Work with the main machine learning algorithms in OpenCV Explore the deep learning Python libraries and OpenCV deep learning capabilities Create computer vision and deep lear...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed May 1, 2019)
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  • 56
    ISBN: 9781789952445 , 1789952441
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Python (Computer program language) ; Computer networks ; Management ; Client/server computing ; Electronic books ; Electronic books ; local
    Abstract: Achieve improved network programmability and automation by leveraging powerful network programming concepts, algorithms, and tools Key Features Deal with remote network servers using SSH, FTP, SNMP and LDAP protocols. Design multi threaded and event-driven architectures for asynchronous servers programming. Leverage your Python programming skills to build powerful network applications Book Description Network programming has always been a demanding task. With full-featured and well-documented libraries all the way up the stack, Python makes network programming the enjoyable experience it should be. Starting with a walk through of today's major networking protocols, through this book, you'll learn how to employ Python for network programming, how to request and retrieve web resources, and how to extract data in major formats over the web. You will utilize Python for emailing using different protocols, and you'll interact with remote systems and IP and DNS networking. You will cover the connection of networking devices and configuration using Python 3.7, along with cloud-based network management tasks using Python. As the book progresses, socket programming will be covered, followed by how to design servers, and the pros and cons of multithreaded and event-driven architectures. You'll develop practical clientside applications, including web API clients, email clients, SSH, and FTP. These applications will also be implemented through existing web application frameworks. What you will learn Execute Python modules on networking tools Automate tasks regarding the analysis and extraction of information from a network Get to grips with asynchronous programming modules available in Python Get to grips with IP address manipulation modules using Python programming Understand the main frameworks available in Python that are focused on web application Manipulate IP addresses and perform CIDR calculations Who this book is for If you're a Python developer or a system administrator with Python experience and you're looking to take your first steps in network programming, then this book is for you. If you're a network engineer or a network professional aiming to be more productive and efficient in networking programmability and automation then this book would serve as a useful resource. Basic knowledge of Python is assumed.
    Note: Previous edition published: 2015. - Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed May 8, 2019)
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  • 57
    ISBN: 9781138546806 , 9781472452467
    Language: English
    Pages: xiv, 234 Seiten , Diagramme , 25 cm
    Edition: First issued in paperback
    Series Statement: International population studies
    DDC: 307.20941
    RVK:
    RVK:
    RVK:
    Keywords: Migration, Internal / Great Britain ; Internal migrants / Social conditions / Great Britain ; Binnenwanderung ; Großbritannien ; Großbritannien ; Aufsatzsammlung ; Großbritannien ; Binnenwanderung
    Note: Includes bibliographical references and index
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  • 58
    ISBN: 9781138295674
    Language: English
    Pages: ix, 128 Seiten , Diagramme
    Series Statement: Ethnic and racial studies
    RVK:
    RVK:
    RVK:
    RVK:
    Keywords: Das Andere ; Ausgrenzung ; Diskriminierung ; Roma ; Großbritannien ; Kanada ; Finnland ; Ungarn ; Ethnic Identity ; Migration ; Racism ; European Union Policy ; Electronic books ; Aufsatzsammlung ; Aufsatzsammlung ; Finnland ; Ungarn ; Großbritannien ; Kanada ; Roma ; Diskriminierung ; Ausgrenzung ; Das Andere
    Abstract: "Using detailed examples from Finland, Hungary, Canada and the UK, this book explores relationships between the racialization and discrimination experienced by heterogeneous European Roma populations, and the processes of everyday bordering embedded in state policies and media discourses. In the context of the long histories of discrimination experienced by Roma people across Europe, the chapters engage with changing EU policies, including the recent tensions between inter-European de-bordering and the selective immigration policies introduced as different states react to EU free movement. Employing an intersectional analysis, the authors capture the perspectives of differentially situated people and associated discourses to examine the continuing racism experienced by European Roma citizens in their interaction with bordering technologies. They examine the homogenizing ‘racial othering’ and construction of Roma as a ‘criminal category’ that co-exists with the differentiations made between ‘indigenous’ and ‘migrant’ Roma central to dominant bordering discourses and the contestations of different Roma populations. Chapters focus on Roma activism and the media, the exclusion of Roma residents via urban regeneration and welfare provision, and powerful media and political discourses about Roma populations in different national and transnational contexts. This book was originally published as a special issue of Ethnic and Racial Studies. "--Provided by publisher
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  • 59
    ISBN: 9781138634640
    Language: English
    Pages: xv, 312 Seiten
    Series Statement: Variorum collected studies series
    DDC: 306.3/62
    Keywords: Slavery History ; Antislavery movements History ; Aufsatzsammlung ; Aufsatzsammlung ; Großbritannien ; Kolonie ; Abolitionismus ; Geschichte
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  • 60
    ISBN: 9781789530636 , 1789530636
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: Architect scalable, reliable, and maintainable applications for enterprises with Python Key Features Explore various Python design patterns used for enterprise software development Apply best practices for testing and performance optimization to build stable applications Learn about different attacking strategies used on enterprise applications and how to avoid them Book Description Dynamically typed languages like Python are continuously improving. With the addition of exciting new features and a wide selection of modern libraries and frameworks, Python has emerged as an ideal language for developing enterprise applications. Hands-On Enterprise Application Development with Python will show you how to build effective applications that are stable, secure, and easily scalable. The book is a detailed guide to building an end-to-end enterprise-grade application in Python. You will learn how to effectively implement Python features and design patterns that will positively impact your application lifecycle. The book also covers advanced concurrency techniques that will help you build a RESTful application with an optimized frontend. Given that security and stability are the foundation for an enterprise application, you'll be trained on effective testing, performance analysis, and security practices, and understand how to embed them in your codebase during the initial phase. You'll also be guided in how to move on from a monolithic architecture to one that is service oriented, leveraging microservices and serverless deployment techniques. By the end of the book, you will have become proficient at building efficient enterprise applications in Python. What you will learn Understand the purpose of design patterns and their impact on application lifecycle Build applications that can handle large amounts of data-intensive operations Uncover advanced concurrency techniques and discover how to handle a large number of requests in production Optimize frontends to improve the client-side experience of your application Effective testing and performance profiling techniques to detect issues in applications early in the development cycle Build applications with a focus on security Implement large applications as microservices to improve scalability Who this book is for If you're a developer who wants to build enterprise-grade applications, this book is for you. Basic to intermediate-level of programming experience with Python and database systems is required to ...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed February 26, 2019)
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  • 61
    ISBN: 9781789341362 , 1789341361
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: Immerse yourself in the world of Python concurrency and tackle the most complex concurrent programming problems Key Features Explore the core syntaxes, language features and modern patterns of concurrency in Python Understand how to use concurrency to keep data consistent and applications responsive Utilize application scaffolding to design highly-scalable programs Book Description Python is one of the most popular programming languages, with numerous libraries and frameworks that facilitate high-performance computing. Concurrency and parallelism in Python are essential when it comes to multiprocessing and multithreading; they behave differently, but their common aim is to reduce the execution time. This book serves as a comprehensive introduction to various advanced concepts in concurrent engineering and programming. Mastering Concurrency in Python starts by introducing the concepts and principles in concurrency, right from Amdahl's Law to multithreading programming, followed by elucidating multiprocessing programming, web scraping, and asynchronous I/O, together with common problems that engineers and programmers face in concurrent programming. Next, the book covers a number of advanced concepts in Python concurrency and how they interact with the Python ecosystem, including the Global Interpreter Lock (GIL). Finally, you'll learn how to solve real-world concurrency problems through examples. By the end of the book, you will have gained extensive theoretical knowledge of concurrency and the ways in which concurrency is supported by the Python language What you will learn Explore the concepts of concurrency in programming Explore the core syntax and features that enable concurrency in Python Understand the correct way to implement concurrency Abstract methods to keep the data consistent in your program Analyze problems commonly faced in concurrent programming Use application scaffolding to design highly-scalable programs Who this book is for This book is for developers who wish to build high-performance applications and learn about signle-core, multicore programming or distributed concurrency. Some experience with Python programming language is assumed.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed January 25, 2019)
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  • 62
    ISBN: 9781788837934 , 1788837932
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Amazon Web Services (Firm) ; Application software ; Development ; Cloud computing ; Application program interfaces (Computer software) ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Master serverless architectures in Python and their implementation, with Zappa on three different frameworks. Key Features Scalable serverless Python web services using Django, Flask, and Pyramid. Learn Asynchronous task execution on AWS Lambda and scheduling using Zappa. Implementing Zappa in a Docker container. Book Description Serverless applications are becoming very popular these days, not just because they save developers the trouble of managing the servers, but also because they provide several other benefits such as cutting heavy costs and improving the overall performance of the application. This book will help you build serverless applications in a quick and efficient way. We begin with an introduction to AWS and the API gateway, the environment for serverless development, and Zappa. We then look at building, testing, and deploying apps in AWS with three different frameworks--Flask, Django, and Pyramid. Setting up a custom domain along with SSL certificates and configuring them with Zappa is also covered. A few advanced Zappa settings are also covered along with securing Zappa with AWS VPC. By the end of the book you will have mastered using three frameworks to build robust and cost-efficient serverless apps in Python. What you will learn Build, test, and deploy a simple web service using AWS CLI Integrate Flask-based Python applications, via AWS CLI configuration Design Rest APIs integrated with Zappa for Flask and Django Create a project in the Pyramid framework and configure it with Zappa Generate SSL Certificates using Amazon Certificate Manager Configure custom domains with AWS Route 53 Create a Docker container similar to AWS Lambda Who this book is for Python Developers who are interested in learning how to develop fast and highly scalable serverless applications in Python, will find this book useful
    Note: Description based on online resource; title from title page (Safari, viewed August 30, 2018)
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  • 63
    ISBN: 9781788834254 , 1788834259
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Application software ; Development ; Python (Computer program language) ; SPARK (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Combine the power of Apache Spark and Python to build effective big data applications About This Book Perform effective data processing, machine learning, and analytics using PySpark Overcome challenges in developing and deploying Spark solutions using Python Explore recipes for efficiently combining Python and Apache Spark to process data Who This Book Is For The PySpark Cookbook is for you if you are a Python developer looking for hands-on recipes for using the Apache Spark 2.x ecosystem in the best possible way. A thorough understanding of Python (and some familiarity with Spark) will help you get the best out of the book. What You Will Learn Configure a local instance of PySpark in a virtual environment Install and configure Jupyter in local and multi-node environments Create DataFrames from JSON and a dictionary using pyspark.sql Explore regression and clustering models available in the ML module Use DataFrames to transform data used for modeling Connect to PubNub and perform aggregations on streams In Detail Apache Spark is an open source framework for efficient cluster computing with a strong interface for data parallelism and fault tolerance. The PySpark Cookbook presents effective and time-saving recipes for leveraging the power of Python and putting it to use in the Spark ecosystem. You'll start by learning the Apache Spark architecture and how to set up a Python environment for Spark. You'll then get familiar with the modules available in PySpark and start using them effortlessly. In addition to this, you'll discover how to abstract data with RDDs and DataFrames, and understand the streaming capabilities of PySpark. You'll then move on to using ML and MLlib in order to solve any problems related to the machine learning capabilities of PySpark and use GraphFrames to solve graph-processing problems. Finally, you will explore how to deploy your applications to the cloud using the spark-submit command. By the end of this book, you will be able to use the Python API for Apache Spark to solve any problems associated with building data-intensive applications. Style and approach This book is a rich collection of recipes that will come in handy when you are working with PySpark Addressing your common and not-so-common pain points, this is a book that you must have on the shelf.
    Note: Description based on online resource; title from title page (Safari, viewed July 30, 2018)
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  • 64
    ISBN: 9781789132823 , 1789132827
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Neural networks (Computer science) ; Machine learning ; Artificial intelligence ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Learn how to apply TensorFlow to a wide range of deep learning and Machine Learning problems with this practical guide on training CNNs for image classification, image recognition, object detection and many computer vision challenges. Key Features Learn the fundamentals of Convolutional Neural Networks Harness Python and Tensorflow to train CNNs Build scalable deep learning models that can process millions of items Book Description Convolutional Neural Networks (CNN) are one of the most popular architectures used in computer vision apps. This book is an introduction to CNNs through solving real-world problems in deep learning while teaching you their implementation in popular Python library - TensorFlow. By the end of the book, you will be training CNNs in no time! We start with an overview of popular machine learning and deep learning models, and then get you set up with a TensorFlow development environment. This environment is the basis for implementing and training deep learning models in later chapters. Then, you will use Convolutional Neural Networks to work on problems such as image classification, object detection, and semantic segmentation. After that, you will use transfer learning to see how these models can solve other deep learning problems. You will also get a taste of implementing generative models such as autoencoders and generative adversarial networks. Later on, you will see useful tips on machine learning best practices and troubleshooting. Finally, you will learn how to apply your models on large datasets of millions of images. What you will learn Train machine learning models with TensorFlow Create systems that can evolve and scale during their life cycle Use CNNs in image recognition and classification Use TensorFlow for building deep learning models Train popular deep learning models Fine-tune a neural network to improve the quality of results with transfer learning Build TensorFlow models that can scale to large datasets and systems Who this book is for This book is for Software Engineers, Data Scientists, or Machine Learning practitioners who want to use CNNs for solving real-world problems. Knowledge of basic machine learning concepts, linear algebra and Python will help.
    Note: Description based on online resource; title from title page (Safari, viewed October 5, 2018)
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  • 65
    ISBN: 9781789134759 , 1789134757
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Machine learning ; Neural networks (Computer science) ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Insightful practical projects to master deep learning and neural network architectures using Python, Keras and MXNet About This Book Rich projects on computer vision, NLP, and image processing Build your own neural network and explore innumerable possibilities with deep learning Explore the power of Python for deep learning in various scenarios using insightful projects Who This Book Is For This book is for developers, data scientists, or enthusiasts, who have sound knowledge of python programming, basics of machine learning, and want to break into deep learning, either for opening a new career opportunity or for realizing their own AI projects. What You Will Learn Set up a Deep Learning development environment on AWS, using GPU-powered instances and the Deep Learning AMI Implement Sequence to Sequence Networks for modeling natural language processing Develop an end-to-end speech recognition system Build a system for pixel-wise semantic labeling of an image Develop a system that generates images and their regions In Detail Deep Learning has quietly revolutionized every field of Artificial Intelligence, enabling the development of applications that a few years ago were considered almost impossible. This book will provide all the knowledge needed to implement complex deep learning projects in the field of computational linguistics and computer vision. Each new project will build upon the experience and knowledge accumulated in the previous ones, allowing the reader to progressively master the subject. You will learn neural network models implementing a text classifier system using Recurrent Neural network model (RNN) and optimize it to understand the shortcomings you might come across while implementing a simple deep learning system. If you are looking to implement intelligent systems like Automatic Machine Translation, Handwriting Generation, Character Text Generation, Object Classification in Photographs, Colorization of Images, Image Caption Generation, Character Text Generation or Automatic Game Playing into your application then this book is for you. By the end of this book, you will come across various Recurrent and Convolutional Neural network implementations with practical hands-on to modeling concepts like regularization, Gradient clipping, and gradient normalization, LSTM, Bidirectional RNN's through a series engaging projects. Style and approach One stop guide to gain deep learning knowledge and skills by working on authentic, engagin...
    Note: Description based on online resource; title from title page (Safari, viewed March 1, 2019)
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  • 66
    ISBN: 9781789533163 , 1789533163
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Electronic funds transfers ; Python (Computer program language) ; Bitcoin ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: Simplified Python programming for Bitcoin and blockchain Key Features Build Bitcoin applications in Python with the help of simple examples Mine Bitcoins, program Bitcoin-enabled APIs and transaction graphs, and build trading bots Analyze Bitcoin transactions and produce visualizations using Python data analysis tools Book Description Bitcoin is a cryptocurrency that's changing the face of online payments. Hands-On Bitcoin Programming with Python teaches you to build software applications for mining and creating Bitcoins using Python. This book starts with the basics of both Bitcoin and blockchain and gives you an overview of these inherent concepts by showing you how to build Bitcoin-driven applications with Python. Packed with clear instructions and practical examples, you will learn to understand simple Python coding examples that work with this cryptocurrency. By the end of the book, you'll be able to mine Bitcoins, accept Bitcoin payments on the app, and work with the basics of blockchain technology to create simply distributed ledgers. What you will learn Master the Bitcoin APIs in Python to manipulate Bitcoin from your Python apps Build your own Bitcoin trading bots to buy Bitcoins at a lower price and sell them at a higher price Write scripts to process Bitcoin payments through a website or app Develop software for Bitcoin mining to create Bitcoin currency on your own computer hardware Create your own keys, addresses, and wallets in Python code Write software to analyze Bitcoin transactions and produce reports, graphs, and other visualizations Who this book is for Hands-On Bitcoin Programming with Python consists of examples that will teach you to build your own Bitcoin application. You will learn to write scripts, build software for mining, and create Bitcoins using Python. Anyone with prior Python experience, who wants to explore Python Bitcoin programming and start building Bitcoin-driven Python apps, will find this book useful.
    Note: Description based on online resource; title from title page (Safari, viewed October 2, 2018)
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  • 67
    ISBN: 9781789534405 , 1789534402
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Data mining ; Python (Computer program language) ; Quantitative research ; Science ; Data processing ; Electronic books ; Electronic books ; local
    Abstract: Enhance your data analysis and predictive modeling skills using popular Python tools Key Features Cover all fundamental libraries for operation and manipulation of Python for data analysis Implement real-world datasets to perform predictive analytics with Python Access modern data analysis techniques and detailed code with scikit-learn and SciPy Book Description Python is one of the most common and popular languages preferred by leading data analysts and statisticians for working with massive datasets and complex data visualizations. Become a Python Data Analyst introduces Python's most essential tools and libraries necessary to work with the data analysis process, right from preparing data to performing simple statistical analyses and creating meaningful data visualizations. In this book, we will cover Python libraries such as NumPy, pandas, matplotlib, seaborn, SciPy, and scikit-learn, and apply them in practical data analysis and statistics examples. As you make your way through the chapters, you will learn to efficiently use the Jupyter Notebook to operate and manipulate data using NumPy and the pandas library. In the concluding chapters, you will gain experience in building simple predictive models and carrying out statistical computation and analysis using rich Python tools and proven data analysis techniques. By the end of this book, you will have hands-on experience performing data analysis with Python. What you will learn Explore important Python libraries and learn to install Anaconda distribution Understand the basics of NumPy Produce informative and useful visualizations for analyzing data Perform common statistical calculations Build predictive models and understand the principles of predictive analytics Who this book is for Become a Python Data Analyst is for entry-level data analysts, data engineers, and BI professionals who want to make complete use of Python tools for performing efficient data analysis. Prior knowledge of Python programming is necessary to understand the concepts covered in this book
    Note: Description based on online resource; title from title page (Safari, viewed October 2, 2018)
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  • 68
    ISBN: 9781789131314 , 1789131316
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Learn how to create interactive and visually aesthetic plots using the Bokeh package in Python About This Book A step by step approach to creating interactive plots with Bokeh Go from nstallation all the way to deploying your very own Bokeh application Work with a real time datasets to practice and create your very own plots and applications Who This Book Is For This book is well suited for data scientists and data analysts who want to perform interactive data visualization on their web browsers using Bokeh. Some exposure to Python programming will be helpful, but prior experience with Bokeh is not required. What You Will Learn Installing Bokeh and understanding its key concepts Creating plots using glyphs, the fundamental building blocks of Bokeh Creating plots using different data structures like NumPy and Pandas Using layouts and widgets to visually enhance your plots and add a layer of interactivity Building and hosting applications on the Bokeh server Creating advanced plots using spatial data In Detail Adding a layer of interactivity to your plots and converting these plots into applications hold immense value in the field of data science. The standard approach to adding interactivity would be to use paid software such as Tableau, but the Bokeh package in Python offers users a way to create both interactive and visually aesthetic plots for free. This book gets you up to speed with Bokeh - a popular Python library for interactive data visualization. The book starts out by helping you understand how Bokeh works internally and how you can set up and install the package in your local machine. You then use a real world data set which uses stock data from Kaggle to create interactive and visually stunning plots. You will also learn how to leverage Bokeh using some advanced concepts such as plotting with spatial and geo data. Finally you will use all the concepts that you have learned in the previous chapters to create your very own Bokeh application from scratch. By the end of the book you will be able to create your very own Bokeh application. You will have gone through a step by step process that starts with understanding what Bokeh actually is and ends with building your very own Bokeh application filled with interactive and visually aesthetic plots. Style and approach This books take you through a step by step process that starts with understanding what Bokeh actually is and ends with building your very own Bokeh application filled with in...
    Note: Description based on online resource; title from title page (Safari, viewed August 28, 2018)
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  • 69
    ISBN: 9781788996846 , 1788996844
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Numerical analysis ; Data processing ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Enhance the power of NumPy and start boosting your scientific computing capabilities About This Book Grasp all aspects of numerical computing and understand NumPy Explore examples to learn exploratory data analysis (EDA), regression, and clustering Access NumPy libraries and use performance benchmarking to select the right tool Who This Book Is For Mastering Numerical Computing with NumPy is for you if you are a Python programmer, data analyst, data engineer, or a data science enthusiast, who wants to master the intricacies of NumPy and build solutions for your numeric and scientific computational problems. You are expected to have familiarity with mathematics to get the most out of this book. What You Will Learn Perform vector and matrix operations using NumPy Perform exploratory data analysis (EDA) on US housing data Develop a predictive model using simple and multiple linear regression Understand unsupervised learning and clustering algorithms with practical use cases Write better NumPy code and implement the algorithms from scratch Perform benchmark tests to choose the best configuration for your system In Detail NumPy is one of the most important scientific computing libraries available for Python. Mastering Numerical Computing with NumPy teaches you how to achieve expert level competency to perform complex operations, with in-depth coverage of advanced concepts. Beginning with NumPy's arrays and functions, you will familiarize yourself with linear algebra concepts to perform vector and matrix math operations. You will thoroughly understand and practice data processing, exploratory data analysis (EDA), and predictive modeling. You will then move on to working on practical examples which will teach you how to use NumPy statistics in order to explore US housing data and develop a predictive model using simple and multiple linear regression techniques. Once you have got to grips with the basics, you will explore unsupervised learning and clustering algorithms, followed by understanding how to write better NumPy code while keeping advanced considerations in mind. The book also demonstrates the use of different high-performance numerical computing libraries and their relationship with NumPy. You will study how to benchmark the performance of different configurations and choose the best for your system. By the end of this book, you will have become an expert in handling and performing complex data manipulations. Style and approach This masterin...
    Note: Description based on online resource; title from title page (Safari, viewed July 27, 2018)
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  • 70
    ISBN: 9781789951721 , 1789951720
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Series Statement: Learning path
    Keywords: Python (Computer program language) ; Artificial intelligence ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Demystify the complexity of machine learning techniques and create evolving, clever solutions to solve your problems Key Features Master supervised, unsupervised, and semi-supervised ML algorithms and their implementation Build deep learning models for object detection, image classification, similarity learning, and more Build, deploy, and scale end-to-end deep neural network models in a production environment Book Description This Learning Path is your complete guide to quickly getting to grips with popular machine learning algorithms. You'll be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this Learning Path will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries. You'll bring the use of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Next, you'll learn the advanced features of TensorFlow1.x, such as distributed TensorFlow with TF clusters, deploy production models with TensorFlow Serving. You'll implement different techniques related to object classification, object detection, image segmentation, and more. By the end of this Learning Path, you'll have obtained in-depth knowledge of TensorFlow, making you the go-to person for solving artificial intelligence problems This Learning Path includes content from the following Packt products: Mastering Machine Learning Algorithms by Giuseppe Bonaccorso Mastering TensorFlow 1.x by Armando Fandango Deep Learning for Computer Vision by Rajalingappaa Shanmugamani What you will learn Explore how an ML model can be trained, optimized, and evaluated Work with Autoencoders and Generative Adversarial Networks Explore the most important Reinforcement Learning techniques Build end-to-end deep learning (CNN, RNN, and Autoencoders) models Who this book is for This Learning Path is for data scientists, machine learning engineers, artificial intelligence engineers who want to delve into complex machine learning algorithms, calibrate models, and improve the predictions of the trained model. You will encounter the advanced intricacies and complex use cases of deep learning and AI. A basic knowledge of programming in Python and some un...
    Note: Description based on online resource; title from cover (Safari, viewed February 22, 2019)
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  • 71
    ISBN: 9781788992534 , 1788992539
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Internet marketing ; Data mining ; Electronic books ; Electronic books ; local
    Abstract: With Hands-On Recommendation Systems with Python, learn the tools and techniques required in building various kinds of powerful recommendation systems (collaborative, knowledge and content based) and deploying them to the web Key Features Build industry-standard recommender systems Only familiarity with Python is required No need to wade through complicated machine learning theory to use this book Book Description Recommendation systems are at the heart of almost every internet business today; from Facebook to Net?ix to Amazon. Providing good recommendations, whether it's friends, movies, or groceries, goes a long way in defining user experience and enticing your customers to use your platform. This book shows you how to do just that. You will learn about the different kinds of recommenders used in the industry and see how to build them from scratch using Python. No need to wade through tons of machine learning theory - you'll get started with building and learning about recommenders as quickly as possible.. In this book, you will build an IMDB Top 250 clone, a content-based engine that works on movie metadata. You'll use collaborative filters to make use of customer behavior data, and a Hybrid Recommender that incorporates content based and collaborative filtering techniques With this book, all you need to get started with building recommendation systems is a familiarity with Python, and by the time you're fnished, you will have a great grasp of how recommenders work and be in a strong position to apply the techniques that you will learn to your own problem domains. What you will learn Get to grips with the different kinds of recommender systems Master data-wrangling techniques using the pandas library Building an IMDB Top 250 Clone Build a content based engine to recommend movies based on movie metadata Employ data-mining techniques used in building recommenders Build industry-standard collaborative filters using powerful algorithms Building Hybrid Recommenders that incorporate content based and collaborative fltering Who this book is for If you are a Python developer and want to develop applications for social networking, news personalization or smart advertising, this is the book for you. Basic knowledge of machine learning techniques will be helpful, but not mandatory.
    Note: Description based on online resource; title from title page (Safari, viewed August 27, 2018)
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  • 72
    ISBN: 9781789612479 , 1789612470
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Artificial intelligence ; Application software ; Development ; Machine learning ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Make your searches more responsive and smarter by applying Artificial Intelligence to it Key Features Enter the world of Artificial Intelligence with solid concepts and real-world use cases Make your applications intelligent using AI in your day-to-day apps and become a smart developer Design and implement artificial intelligence in searches Book Description With the emergence of big data and modern technologies, AI has acquired a lot of relevance in many domains. The increase in demand for automation has generated many applications for AI in fields such as robotics, predictive analytics, finance, and more. In this book, you will understand what artificial intelligence is. It explains in detail basic search methods: Depth-First Search (DFS), Breadth-First Search (BFS), and A* Search, which can be used to make intelligent decisions when the initial state, end state, and possible actions are known. Random solutions or greedy solutions can be found for such problems. But these are not optimal in either space or time and efficient approaches in time and space will be explored. We will also understand how to formulate a problem, which involves looking at it and identifying its initial state, goal state, and the actions that are possible in each state. We also need to understand the data structures involved while implementing these search algorithms as they form the basis of search exploration. Finally, we will look into what a heuristic is as this decides the quality of one sub-solution over another and helps you decide which step to take. What you will learn Understand the instances where searches can be used Understand the algorithms that can be used to make decisions more intelligent Formulate a problem by specifying its initial state, goal state, and actions Translate the concepts of the selected search algorithm into code Compare how basic search algorithms will perform for the application Implement algorithmic programming using code examples Who this book is for This book is for developers who are keen to get started with Artificial Intelligence and develop practical AI-based applications. Those developers who want to upgrade their normal applications to smart and intelligent versions will find this book useful. A basic knowledge and understanding of Python are assumed.
    Note: Description based on online resource; title from title page (Safari, viewed October 8, 2018)
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  • 73
    ISBN: 9781789533538 , 1789533538
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Kick-start your development journey with this end-to-end guide that covers Python programming fundamentals along with application development Key Features Gain a solid understanding of Python programming with coverage of data structures and Object-Oriented Programming (OOP) Design graphical user interfaces for desktops with libraries such as Kivy and Tkinter Write elegant, reusable, and efficient code Book Description Python is a cross-platform language used by organizations such as Google and NASA. It lets you work quickly and efficiently, allowing you to concentrate on your work rather than the language. Based on his personal experiences when learning to program, Learn Programming in Python with Cody Jackson provides a hands-on introduction to computer programming utilizing one of the most readable programming languages?Python. It aims to educate readers regarding software development as well as help experienced developers become familiar with the Python language, utilizing real-world lessons to help readers understand programming concepts quickly and easily. The book starts with the basics of programming, and describes Python syntax while developing the skills to make complete programs. In the first part of the book, readers will be going through all the concepts with short and easy-to-understand code samples that will prepare them for the comprehensive application built in parts 2 and 3. The second part of the book will explore topics such as application requirements, building the application, testing, and documentation. It is here that you will get a solid understanding of building an end-to-end application in Python. The next part will show you how to complete your applications by converting text-based simulation into an interactive, graphical user interface, using a desktop GUI framework. After reading the book, you will be confident in developing a complete application in Python, from program design to documentation to deployment. What you will learn Use the interactive shell for prototyping and code execution, including variable assignment Deal with program errors by learning when to manually throw exceptions Employ exceptions for code management Enhance code by utilizing Python's built-in shortcuts to improve efficiency and make coding easier Interact with files and package Python data for network transfer or storage Understand how tests drive code writing, and vice versa Explore the different frameworks that are available for GUI de...
    Note: Description based on online resource; title from title page (Safari, viewed March 8, 2019)
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  • 74
    Online Resource
    Online Resource
    Birmingham, UK : Packt Publishing
    ISBN: 9781789951929 , 1789951925
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Machine learning ; Information visualization ; Electronic data processing ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Become the master player of data exploration by creating reproducible data processing pipelines, visualizations, and prediction models for your applications. Key Features Get up and running with the Jupyter ecosystem and some example datasets Learn about key machine learning concepts such as SVM, KNN classifiers, and Random Forests Discover how you can use web scraping to gather and parse your own bespoke datasets Book Description Getting started with data science doesn't have to be an uphill battle. Applied Data Science with Python and Jupyter is a step-by-step guide ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction to these concepts. In this book, you'll learn every aspect of the standard data workflow process, including collecting, cleaning, investigating, visualizing, and modeling data. You'll start with the basics of Jupyter, which will be the backbone of the book. After familiarizing ourselves with its standard features, you'll look at an example of it in practice with our first analysis. In the next lesson, you dive right into predictive analytics, where multiple classification algorithms are implemented. Finally, the book ends by looking at data collection techniques. You'll see how web data can be acquired with scraping techniques and via APIs, and then briefly explore interactive visualizations. What you will learn Get up and running with the Jupyter ecosystem Identify potential areas of investigation and perform exploratory data analysis Plan a machine learning classification strategy and train classification models Use validation curves and dimensionality reduction to tune and enhance your models Scrape tabular data from web pages and transform it into Pandas DataFrames Create interactive, web-friendly visualizations to clearly communicate your findings Who this book is for Applied Data Science with Python and Jupyter is ideal for professionals with a variety of job descriptions across a large range of industries, given the rising popularity and accessibility of data science. You'll need some prior experience with Python, with any prior work with libraries such as Pandas, Matplotlib, and Pandas providing you a useful head start.
    Note: Description based on online resource; title from copyright page (Safari, viewed June 12, 2019)
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  • 75
    ISBN: 9781789957228 , 1789957222
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Series Statement: Learning path
    Keywords: Python (Computer program language) ; Data mining ; Information visualization ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Understand, explore, and effectively present data using the powerful data visualization techniques of Python Key Features Use the power of Pandas and Matplotlib to easily solve data mining issues Understand the basics of statistics to build powerful predictive data models Grasp data mining concepts with helpful use-cases and examples Book Description Data mining, or parsing the data to extract useful insights, is a niche skill that can transform your career as a data scientist Python is a flexible programming language that is equipped with a strong suite of libraries and toolkits, and gives you the perfect platform to sift through your data and mine the insights you seek. This Learning Path is designed to familiarize you with the Python libraries and the underlying statistics that you need to get comfortable with data mining. You will learn how to use Pandas, Python's popular library to analyze different kinds of data, and leverage the power of Matplotlib to generate appealing and impressive visualizations for the insights you have derived. You will also explore different machine learning techniques and statistics that enable you to build powerful predictive models. By the end of this Learning Path, you will have the perfect foundation to take your data mining skills to the next level and set yourself on the path to become a sought-after data science professional. This Learning Path includes content from the following Packt products: Statistics for Machine Learning by Pratap Dangeti Matplotlib 2.x By Example by Allen Yu, Claire Chung, Aldrin Yim Pandas Cookbook by Theodore Petrou What you will learn Understand the statistical fundamentals to build data models Split data into independent groups Apply aggregations and transformations to each group Create impressive data visualizations Prepare your data and design models Clean up data to ease data analysis and visualization Create insightful visualizations with Matplotlib and Seaborn Customize the model to suit your own predictive goals Who this book is for If you want to learn how to use the many libraries of Python to extract impactful information from your data and present it as engaging visuals, then this is the ideal Learning Path for you. Some basic knowledge of Python is enough to get started with this Learning Path.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed February 20, 2019)
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  • 76
    ISBN: 9781789806991 , 1789806992
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: A hands-on guide to deep learning that's filled with intuitive explanations and engaging practical examples Key Features Designed to iteratively develop the skills of Python users who don't have a data science background Covers the key foundational concepts you'll need to know when building deep learning systems Full of step-by-step exercises and activities to help build the skills that you need for the real-world Book Description Taking an approach that uses the latest developments in the Python ecosystem, you'll first be guided through the Jupyter ecosystem, key visualization libraries and powerful data sanitization techniques before we train our first predictive model. We'll explore a variety of approaches to classification like support vector networks, random decision forests and k-nearest neighbours to build out your understanding before we move into more complex territory. It's okay if these terms seem overwhelming; we'll show you how to put them to work. We'll build upon our classification coverage by taking a quick look at ethical web scraping and interactive visualizations to help you professionally gather and present your analysis. It's after this that we start building out our keystone deep learning application, one that aims to predict the future price of Bitcoin based on historical public data. By guiding you through a trained neural network, we'll explore common deep learning network architectures (convolutional, recurrent, generative adversarial) and branch out into deep reinforcement learning before we dive into model optimization and evaluation. We'll do all of this whilst working on a production-ready web application that combines Tensorflow and Keras to produce a meaningful user-friendly result, leaving you with all the skills you need to tackle and develop your own real-world deep learning projects confidently and effectively. What you will learn Discover how you can assemble and clean your very own datasets Develop a tailored machine learning classification strategy Build, train and enhance your own models to solve unique problems Work with production-ready frameworks like Tensorflow and Keras Explain how neural networks operate in clear and simple terms Understand how to deploy your predictions to the web Who this book is for If you're a Python programmer stepping into the world of data science, this is the ideal way to get started.
    Note: Description based on online resource; title from title page (Safari, viewed December 3, 2018)
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  • 77
    ISBN: 9781789618174 , 1789618177
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Understand and build beautiful and advanced plots with Matplotlib and Python Key Features Practical guide with hands-on examples to design interactive plots Advanced techniques to constructing complex plots Explore 3D plotting and visualization using Jupyter Notebook Book Description In this book, you'll get hands-on with customizing your data plots with the help of Matplotlib. You'll start with customizing plots, making a handful of special-purpose plots, and building 3D plots. You'll explore non-trivial layouts, Pylab customization, and more about tile configuration. You'll be able to add text, put lines in plots, and also handle polygons, shapes, and annotations. Non-Cartesian and vector plots are exciting to construct, and you'll explore them further in this book. You'll delve into niche plots and visualize ordinal and tabular data. In this book, you'll be exploring 3D plotting, one of the best features when it comes to 3D data visualization, along with Jupyter Notebook, widgets, and creating movies for enhanced data representation. Geospatial plotting will also be explored. Finally, you'll learn how to create interactive plots with the help of Jupyter. Learn expert techniques for effective data visualization using Matplotlib 3 and Python with our latest offering -- Matplotlib 3.0 Cookbook What you will learn Deal with non-trivial and unusual plots Understanding Basemap methods Customize and represent data in 3D Construct Non-Cartesian and vector plots Design interactive plots using Jupyter Notebook Make movies for enhanced data representation Who this book is for This book is aimed at individuals who want to explore data visualization techniques. A basic knowledge of Matplotlib and Python is required.
    Note: Description based on online resource; title from title page (Safari, viewed February 14, 2019)
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  • 78
    ISBN: 9781789531893 , 1789531896
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Third edition.
    Keywords: Python (Computer program language) ; Database management ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Gain useful insights from your data using popular data science tools Key Features A one-stop guide to Python libraries such as pandas and NumPy Comprehensive coverage of data science operations such as data cleaning and data manipulation Choose scalable learning algorithms for your data science tasks Book Description Fully expanded and upgraded, the latest edition of Python Data Science Essentials will help you succeed in data science operations using the most common Python libraries. This book offers up-to-date insight into the core of Python, including the latest versions of the Jupyter Notebook, NumPy, pandas, and scikit-learn. The book covers detailed examples and large hybrid datasets to help you grasp essential statistical techniques for data collection, data munging and analysis, visualization, and reporting activities. You will also gain an understanding of advanced data science topics such as machine learning algorithms, distributed computing, tuning predictive models, and natural language processing. Furthermore, You'll also be introduced to deep learning and gradient boosting solutions such as XGBoost, LightGBM, and CatBoost. By the end of the book, you will have gained a complete overview of the principal machine learning algorithms, graph analysis techniques, and all the visualization and deployment instruments that make it easier to present your results to an audience of both data science experts and business users What you will learn Set up your data science toolbox on Windows, Mac, and Linux Use the core machine learning methods offered by the scikit-learn library Manipulate, fix, and explore data to solve data science problems Learn advanced explorative and manipulative techniques to solve data operations Optimize your machine learning models for optimized performance Explore and cluster graphs, taking advantage of interconnections and links in your data Who this book is for If you're a data science entrant, data analyst, or data engineer, this book will help you get ready to tackle real-world data science problems without wasting any time. Basic knowledge of probability/statistics and Python coding experience will assist you in understanding the concepts covered in this book. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support an...
    Note: Description based on online resource; title from title page (viewed November 5, 2018)
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  • 79
    ISBN: 9781789537949 , 1789537940
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Cryptography ; Ciphers ; Data encryption (Computer science) ; Electronic books ; Electronic books ; local
    Abstract: Learn to evaluate and compare data encryption methods and attack cryptographic systems About This Book Explore popular and important cryptographic methods Compare cryptographic modes and understand their limitations Learn to perform attacks on cryptographic systems Who This Book Is For Hands-On Cryptography with Python is for security professionals who want to learn to encrypt and evaluate data, and compare different encryption methods. What You Will Learn Protect data with encryption and hashing Explore and compare various encryption methods Encrypt data using the Caesar Cipher technique Make hashes and crack them Learn how to use three NIST-recommended systems: AES, SHA, and RSA Understand common errors in encryption and exploit them In Detail Cryptography is essential for protecting sensitive information, but it is often performed inadequately or incorrectly. Hands-On Cryptography with Python starts by showing you how to encrypt and evaluate your data. The book will then walk you through various data encryption methods,such as obfuscation, hashing, and strong encryption, and will show how you can attack cryptographic systems. You will learn how to create hashes, crack them, and will understand why they are so different from each other. In the concluding chapters, you will use three NIST-recommended systems: the Advanced Encryption Standard (AES), the Secure Hash Algorithm (SHA), and the Rivest-Shamir-Adleman (RSA). By the end of this book, you will be able to deal with common errors in encryption. Style and approach A practical guide that will help the readers to encrypt their data with ease
    Note: Description based on online resource; title from title page (Safari, viewed August 1, 2018)
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  • 80
    ISBN: 9781789137446 , 1789137446
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Science ; Data processing ; Data mining ; Information visualization ; Python (Computer program language) ; Java (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Create and share livecode, equations, visualizations, and explanatory text, in both a single document and a web browser with Jupyter Key Features Learn how to use Jupyter 5.x features such as cell tagging and attractive table styles Leverage big data tools and datasets with different Python packages Explore multiple-user Jupyter Notebook servers Book Description The Jupyter Notebook allows you to create and share documents that contain live code, equations, visualizations, and explanatory text. The Jupyter Notebook system is extensively used in domains such as data cleaning and transformation, numerical simulation, statistical modeling, and machine learning. Learning Jupyter 5 will help you get to grips with interactive computing using real-world examples. The book starts with a detailed overview of the Jupyter Notebook system and its installation in different environments. Next, you will learn to integrate the Jupyter system with different programming languages such as R, Python, Java, JavaScript, and Julia, and explore various versions and packages that are compatible with the Notebook system. Moving ahead, you will master interactive widgets and namespaces and work with Jupyter in a multi-user mode. By the end of this book, you will have used Jupyter with a big dataset and be able to apply all the functionalities you've explored throughout the book. You will also have learned all about the Jupyter Notebook and be able to start performing data transformation, numerical simulation, and data visualization. What you will learn Install and run the Jupyter Notebook system on your machine Implement programming languages such as R, Python, Julia, and JavaScript with the Jupyter Notebook Use interactive widgets to manipulate and visualize data in real time Start sharing your Notebook with colleagues Invite your colleagues to work with you on the same Notebook Organize your Notebook using Jupyter namespaces Access big data in Jupyter for dealing with large datasets using Spark Who this book is for Learning Jupyter 5 is for developers, data scientists, machine learning users, and anyone working on data analysis or data science projects across different teams. Data science professionals will also find this book useful for performing technical and scientific computing collaboratively. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If ...
    Note: Previous edition published: 2016. - Description based on online resource; title from title page (Safari, viewed October 5, 2018)
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  • 81
    ISBN: 9781789130263 , 1789130263
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Python (Computer program language) ; Application software ; Development ; Computer networks ; Management ; Electronic books ; Electronic books ; local
    Abstract: Master the art of using Python for a diverse range of network engineering tasks Key Features Explore the power of Python libraries to tackle difficult network problems efficiently and effectively Use Python for network device automation, DevOps, and software-defined networking Become an expert in implementing advanced network-related tasks with Python Book Description Networks in your infrastructure set the foundation for how your application can be deployed, maintained, and serviced. Python is the ideal language for network engineers to explore tools that were previously available to systems engineers and application developers. In this second edition of Mastering Python Networking, you'll embark on a Python-based journey to transition from traditional network engineers to network developers ready for the next-generation of networks. This book begins by reviewing the basics of Python and teaches you how Python can interact with both legacy and API-enabled network devices. As you make your way through the chapters, you will then learn to leverage high-level Python packages and frameworks to perform network engineering tasks for automation, monitoring, management, and enhanced security. In the concluding chapters, you will use Jenkins for continuous network integration as well as testing tools to verify your network. By the end of this book, you will be able to perform all networking tasks with ease using Python. What you will learn Use Python libraries to interact with your network Integrate Ansible 2.5 using Python to control Cisco, Juniper, and Arista eAPI network devices Leverage existing frameworks to construct high-level APIs Learn how to build virtual networks in the AWS Cloud Understand how Jenkins can be used to automatically deploy changes in your network Use PyTest and Unittest for Test-Driven Network Development Who this book is for Mastering Python Networking is for network engineers and programmers who want to use Python for networking. Basic familiarity with Python programming and networking-related concepts such as Transmission Control Protocol/Internet Protocol (TCP/IP) will be useful. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.
    Note: Previous edition published: 2017. - Description based on online resource; title from title page (Safari, viewed September 20, 2018)
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  • 82
    ISBN: 9781789347371 , 1789347378
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Machine learning ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Deploy supervised and unsupervised machine learning algorithms using scikit-learn to perform classification, regression, and clustering. Key Features Build your first machine learning model using scikit-learn Train supervised and unsupervised models using popular techniques such as classification, regression and clustering Understand how scikit-learn can be applied to different types of machine learning problems Book Description Scikit-learn is a robust machine learning library for the Python programming language. It provides a set of supervised and unsupervised learning algorithms. This book is the easiest way to learn how to deploy, optimize, and evaluate all of the important machine learning algorithms that scikit-learn provides. This book teaches you how to use scikit-learn for machine learning. You will start by setting up and configuring your machine learning environment with scikit-learn. To put scikit-learn to use, you will learn how to implement various supervised and unsupervised machine learning models. You will learn classification, regression, and clustering techniques to work with different types of datasets and train your models. Finally, you will learn about an effective pipeline to help you build a machine learning project from scratch. By the end of this book, you will be confident in building your own machine learning models for accurate predictions. What you will learn Learn how to work with all scikit-learn's machine learning algorithms Install and set up scikit-learn to build your first machine learning model Employ Unsupervised Machine Learning Algorithms to cluster unlabelled data into groups Perform classification and regression machine learning Use an effective pipeline to build a machine learning project from scratch Who this book is for This book is for aspiring machine learning developers who want to get started with scikit-learn. Intermediate knowledge of Python programming and some fundamental knowledge of linear algebra and probability will help.
    Note: Description based on online resource; title from title page (viewed January 7, 2019)
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  • 83
    ISBN: 9781788992640 , 1788992644
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Computer networks ; Management ; Automation ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Invent your own Python scripts to automate your infrastructure About This Book Make the most of Python libraries and modules to automate your infrastructure Leverage Python programming to automate server configurations and administration tasks Efficiently develop your Python skill set Who This Book Is For Hands-On Enterprise Automation with Python is for system administrators and DevOps engineers who are looking for an alternative to major automation frameworks such as Puppet and Chef. Basic programming knowledge with Python and Linux shell scripting is necessary. What You Will Learn Understand common automation modules used in Python Develop Python scripts to manage network devices Automate common Linux administration tasks with Ansible and Fabric Managing Linux processes Administrate VMware, OpenStack, and AWS instances with Python Security automation and sharing code on GitHub In Detail Hands-On Enterprise Automation with Python starts by covering the set up of a Python environment to perform automation tasks, as well as the modules, libraries, and tools you will be using. We'll explore examples of network automation tasks using simple Python programs and Ansible. Next, we will walk you through automating administration tasks with Python Fabric, where you will learn to perform server configuration and administration, along with system administration tasks such as user management, database management, and process management. As you progress through this book, you'll automate several testing services with Python scripts and perform automation tasks on virtual machines and cloud infrastructure with Python. In the concluding chapters, you will cover Python-based offensive security tools and learn how to automate your security tasks. By the end of this book, you will have mastered the skills of automating several system administration tasks with Python. Style and approach This book will follow a practical approach to help you script and automate tasks using Python. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.
    Note: Description based on online resource; title from title page (Safari, viewed August 8, 2018)
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  • 84
    ISBN: 9781788999557 , 178899955X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Application software ; Development ; Web applications ; Web site development ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Learn to build modern, secure, highly available web MVC applications and API's using Python`s Flask framework. Key Features Create production-ready MVC and REST API with the dynamic features of Flask Utilize the various extensions like Flask-JWT and Flask-SQLAlchemy to develop powerful applications Deploy your flask application on real-world platforms like AWS and Heroku on VM's or Docker containers Book Description Flask is a popular Python framework known for its lightweight and modular design. Mastering Flask Web Development will take you on a complete tour of the Flask environment and teach you how to build a production-ready application. You'll begin by learning about the installation of Flask and basic concepts such as MVC and accessing a database using an ORM. You will learn how to structure your application so that it can scale to any size with the help of Flask Blueprints. You'll then learn how to use Jinja2 templates with a high level of expertise. You will also learn how to develop with SQL or NoSQL databases, and how to develop REST APIs and JWT authentication. Next, you'll move on to build role-based access security and authentication using LDAP, OAuth, OpenID, and database. Also learn how to create asynchronous tasks that can scale to any load using Celery and RabbitMQ or Redis. You will also be introduced to a wide range of Flask extensions to leverage technologies such as cache, localization, and debugging. You will learn how to build your own Flask extensions, how to write tests, and how to get test coverage reports. Finally, you will learn how to deploy your application on Heroku and AWS using various technologies, such as Docker, CloudFormation, and Elastic Beanstalk, and will also learn how to develop Jenkins pipelines to build, test, and deploy applications. What you will learn Develop a Flask extension using best practices Implement various authentication methods: LDAP, JWT, Database, OAuth, and OpenID Learn how to develop role-based access security and become an expert on Jinja2 templates Build tests for your applications and APIs Install and configure a distributed task queue using Celery and RabbitMQ Develop RESTful APIs and secure REST API's Deploy highly available applications that scale on Heroku and AWS using Docker or VMs Who this book is for The ideal target audience for this book would be Python developers who want to use Flask and its advanced features to create Enterprise grade and lightweight applications. Th...
    Note: Previous edition published: 2015. - Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 25, 2019)
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  • 85
    ISBN: 9781788991650 , 1788991656
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Python (Computer program language) ; Electronic books ; local ; Electronic books
    Abstract: Learn the fundamentals of Python (3.7) and how to apply it to data science, programming, and web development. Fully updated to include hands-on tutorials and projects. Key Features Learn the fundamentals of Python programming with interactive projects Apply Python to data science with tools such as IPython and Jupyter Utilize Python for web development and build a real-world app using Django Book Description Learn Python Programming is a quick, thorough, and practical introduction to Python - an extremely flexible and powerful programming language that can be applied to many disciplines. Unlike other books, it doesn't bore you with elaborate explanations of the basics but gets you up-and-running, using the language. You will begin by learning the fundamentals of Python so that you have a rock-solid foundation to build upon. You will explore the foundations of Python programming and learn how Python can be manipulated to achieve results. Explore different programming paradigms and find the best approach to a situation; understand how to carry out performance optimization and effective debugging; control the flow of a program; and utilize an interchange format to exchange data. You'll also walk through cryptographic services in Python and understand secure tokens. Learn Python Programming will give you a thorough understanding of the Python language. You'll learn how to write programs, build websites, and work with data by harnessing Python's renowned data science libraries. Filled with real-world examples and projects, the book covers various types of applications, and concludes by building real-world projects based on the concepts you have learned. What you will learn Get Python up and running on Windows, Mac, and Linux Explore fundamental concepts of coding using data structures and control flow Write elegant, reusable, and efficient code in any situation Understand when to use the functional or OOP approach Cover the basics of security and concurrent/asynchronous programming Create bulletproof, reliable software by writing tests Build a simple website in Django Fetch, clean, and manipulate data Who this book is for Learn Python Programming is for individuals with relatively little experience in coding or Python. It's also ideal for aspiring programmers who need to write scripts or programs to accomplish tasks. The book shows you how to create a full-fledged application. Downloading the example code for this book You can download the example ...
    Note: Previous edition published: 2015. - Description based on online resource; title from title page (Safari, viewed July 31, 2018)
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  • 86
    ISBN: 9781788994101 , 1788994108
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Natural language processing (Computer science) ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Build and deploy intelligent applications for natural language processing with Python by using industry standard tools and recently popular methods in deep learning Key Features A no-math, code-driven programmer's guide to text processing and NLP Get state of the art results with modern tooling across linguistics, text vectors and machine learning Fundamentals of NLP methods from spaCy, gensim, scikit-learn and PyTorch Book Description NLP in Python is among the most sought after skills among data scientists. With code and relevant case studies, this book will show how you can use industry-grade tools to implement NLP programs capable of learning from relevant data. We will explore many modern methods ranging from spaCy to word vectors that have reinvented NLP. The book takes you from the basics of NLP to building text processing applications. We start with an introduction to the basic vocabulary along with a work?ow for building NLP applications. We use industry-grade NLP tools for cleaning and pre-processing text, automatic question and answer generation using linguistics, text embedding, text classifier, and building a chatbot. With each project, you will learn a new concept of NLP. You will learn about entity recognition, part of speech tagging and dependency parsing for Q and A. We use text embedding for both clustering documents and making chatbots, and then build classifiers using scikit-learn. We conclude by deploying these models as REST APIs with Flask. By the end, you will be confident building NLP applications, and know exactly what to look for when approaching new challenges. What you will learn Understand classical linguistics in using English grammar for automatically generating questions and answers from a free text corpus Work with text embedding models for dense number representations of words, subwords and characters in the English language for exploring document clustering Deep Learning in NLP using PyTorch with a code-driven introduction to PyTorch Using an NLP project management Framework for estimating timelines and organizing your project into stages Hack and build a simple chatbot application in 30 minutes Deploy an NLP or machine learning application using Flask as RESTFUL APIs Who this book is for Programmers who wish to build systems that can interpret language. Exposure to Python programming is required. Familiarity with NLP or machine learning vocabulary will be helpful, but not mandatory.
    Note: Description based on online resource; title from title page (viewed February 5, 2019)
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  • 87
    ISBN: 9781788836913 , 178883691X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Reinforcement learning ; Electronic books ; Electronic books ; local
    Abstract: A hands-on guide enriched with examples to master deep reinforcement learning algorithms with Python About This Book Your entry point into the world of artificial intelligence using the power of Python An example-rich guide to master various RL and DRL algorithms Explore various state-of-the-art architectures along with math Who This Book Is For If you're a machine learning developer or deep learning enthusiast interested in artificial intelligence and want to learn about reinforcement learning from scratch, this book is for you. Some knowledge of linear algebra, calculus, and the Python programming language will help you understand the concepts covered in this book. What You Will Learn Understand the basics of reinforcement learning methods, algorithms, and elements Train an agent to walk using OpenAI Gym and Tensorflow Understand the Markov Decision Process, Bellman's optimality, and TD learning Solve multi-armed-bandit problems using various algorithms Master deep learning algorithms, such as RNN, LSTM, and CNN with applications Build intelligent agents using the DRQN algorithm to play the Doom game Teach agents to play the Lunar Lander game using DDPG Train an agent to win a car racing game using dueling DQN In Detail Reinforcement Learning (RL) is the trending and most promising branch of artificial intelligence. Hands-On Reinforcement learning with Python will help you master not only the basic reinforcement learning algorithms but also the advanced deep reinforcement learning algorithms. The book starts with an introduction to Reinforcement Learning followed by OpenAI Gym, and TensorFlow. You will then explore various RL algorithms and concepts, such as Markov Decision Process, Monte Carlo methods, and dynamic programming, including value and policy iteration. This example-rich guide will introduce you to deep reinforcement learning algorithms, such as Dueling DQN, DRQN, A3C, PPO, and TRPO. You will also learn about imagination-augmented agents, learning from human preference, DQfD, HER, and many more of the recent advancements in reinforcement learning. By the end of the book, you will have all the knowledge and experience needed to implement reinforcement learning and deep reinforcement learning in your projects, and you will be all set to enter the world of artificial intelligence. Style and approach This is a hands-on book designed to further expand your machine learning skills by understanding reinforcement to deep reinforcement le...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed August 2, 2018)
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  • 88
    Online Resource
    Online Resource
    Birmingham, UK : Packt Publishing
    ISBN: 9781788837064 , 1788837061
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Python (Computer program language) ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: Getting the most out of Python to improve your codebase Key Features Save maintenance costs by learning to fix your legacy codebase Learn the principles and techniques of refactoring Apply microservices to your legacy systems by implementing practical techniques Book Description Python is currently used in many different areas such as software construction, systems administration, and data processing. In all of these areas, experienced professionals can find examples of inefficiency, problems, and other perils, as a result of bad code. After reading this book, readers will understand these problems, and more importantly, how to correct them. The book begins by describing the basic elements of writing clean code and how it plays an important role in Python programming. You will learn about writing efficient and readable code using the Python standard library and best practices for software design. You will learn to implement the SOLID principles in Python and use decorators to improve your code. The book delves more deeply into object oriented programming in Python and shows you how to use objects with descriptors and generators. It will also show you the design principles of software testing and how to resolve software problems by implementing design patterns in your code. In the final chapter we break down a monolithic application to a microservice one, starting from the code as the basis for a solid platform. By the end of the book, you will be proficient in applying industry approved coding practices to design clean, sustainable and readable Python code. What you will learn Set up tools to effectively work in a development environment Explore how the magic methods of Python can help us write better code Examine the traits of Python to create advanced object-oriented design Understand removal of duplicated code using decorators and descriptors Effectively refactor code with the help of unit tests Learn to implement the SOLID principles in Python Who this book is for This book will appeal to team leads, software architects and senior software engineers who would like to work on their legacy systems to save cost and improve efficiency. A strong understanding of Programming is assumed. Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://www.PacktPub.com. If you purchased this book elsewhere, you can visit http://www.PacktPub.com/support and registe...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed September 19, 2018)
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  • 89
    ISBN: 9781788621854 , 1788621859
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Second edition.
    Keywords: Python (Computer program language) ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: Create succinct and expressive implementations with functional programming in Python About This Book Learn how to choose between imperative and functional approaches based on expressiveness, clarity, and performance Get familiar with complex concepts such as monads, concurrency, and immutability Apply functional Python to common Exploratory Data Analysis (EDA) programming problems Who This Book Is For This book is for Python developers who would like to perform Functional programming with Python. Python Programming knowledge is assumed. What You Will Learn Use Python's generator functions and generator expressions to work with collections in a non-strict (or lazy) manner Utilize Python library modules including itertools, functools, multiprocessing, and concurrent features to ensure efficient functional programs Use Python strings with object-oriented suffix notation and prefix notation Avoid stateful classes with families of tuples Design and implement decorators to create composite functions Use functions such as max(), min(), map(), filter(), and sorted() Write higher-order functions In Detail If you're a Python developer who wants to discover how to take the power of functional programming (FP) and bring it into your own programs, then this book is essential for you, even if you know next to nothing about the paradigm. Starting with a general overview of functional concepts, you'll explore common functional features such as first-class and higher-order functions, pure functions, and more. You'll see how these are accomplished in Python 3.6 to give you the core foundations you'll build upon. After that, you'll discover common functional optimizations for Python to help your apps reach even higher speeds. You'll learn FP concepts such as lazy evaluation using Python's generator functions and expressions. Moving forward, you'll learn to design and implement decorators to create composite functions. You'll also explore data preparation techniques and data exploration in depth, and see how the Python standard library fits the functional programming model. Finally, to top off your journey into the world of functional Python, you'll at look at the PyMonad project and some larger examples to put everything into perspective. Style and approach This book provides a general overview of functional concepts and then delves deeper into the functional features, showing you how the Python standard library fits the functional programming model. It also dem...
    Note: Previous edition published: 2015. - Description based on online resource; title from title page (Safari, viewed May 16, 2018)
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  • 90
    ISBN: 9781788622226 , 1788622227
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Third edition.
    Keywords: Python (Computer program language) ; Machine learning ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Get more from your data by creating practical machine learning systems with Python Key Features Develop your own Python-based machine learning system Discover how Python offers multiple algorithms for modern machine learning systems Explore key Python machine learning libraries to implement in your projects Book Description Machine learning allows systems to learn things without being explicitly programmed to do so. Python is one of the most popular languages used to develop machine learning applications, which take advantage of its extensive library support. This third edition of Building Machine Learning Systems with Python addresses recent developments in the field by covering the most-used datasets and libraries to help you build practical machine learning systems. Using machine learning to gain deeper insights from data is a key skill required by modern application developers and analysts alike. Python, being a dynamic language, allows for fast exploration and experimentation. This book shows you exactly how to find patterns in your raw data. You will start by brushing up on your Python machine learning knowledge and being introduced to libraries. You'll quickly get to grips with serious, real-world projects on datasets, using modeling and creating recommendation systems. With Building Machine Learning Systems with Python, you'll gain the tools and understanding required to build your own systems, all tailored to solve real-world data analysis problems. By the end of this book, you will be able to build machine learning systems using techniques and methodologies such as classification, sentiment analysis, computer vision, reinforcement learning, and neural networks. What you will learn Build a classification system that can be applied to text, images, and sound Employ Amazon Web Services (AWS) to run analysis on the cloud Solve problems related to regression using scikit-learn and TensorFlow Recommend products to users based on their past purchases Understand different ways to apply deep neural networks on structured data Address recent developments in the field of computer vision and reinforcement learning Who this book is for Building Machine Learning Systems with Python is for data scientists, machine learning developers, and Python developers who want to learn how to build increasingly complex machine learning systems. You will use Python's machine learning capabilities to develop effective solutions. Prior knowledge of Python progr...
    Note: Previous edition published: 2015. - Description based on online resource; title from title page (Safari, viewed August 27, 2018)
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  • 91
    ISBN: 9781788835688 , 1788835689
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Graphical user interfaces (Computer systems) ; Programming ; Python (Computer program language) ; Object-oriented programming (Computer science) ; Electronic books ; Electronic books ; local
    Abstract: Find out how to create visually stunning and feature-rich applications by empowering Python's built-in Tkinter GUI toolkit About This Book Explore Tkinter's powerful features to easily design and customize your GUI application Learn the basics of 2D and 3D animation in GUI applications. Learn to integrate stunning Data Visualizations using Tkinter Canvas and Matplotlib. Who This Book Is For This book will appeal to developers and programmers who would like to build GUI-based applications. Knowledge of Python is a prerequisite. What You Will Learn Implement the tools provided by Tkinter to design beautiful GUIs Discover cross-platform development through minor customizations in your existing application Visualize graphs in real time as data comes in using Tkinter's animation capabilities Use PostgreSQL authentication to ensure data security for your application Write unit tests to avoid regressions when updating code In Detail Tkinter is a lightweight, portable, and easy-to-use graphical toolkit available in the Python Standard Library, widely used to build Python GUIs due to its simplicity and availability. This book teaches you to design and build graphical user interfaces that are functional, appealing, and user-friendly using the powerful combination of Python and Tkinter. After being introduced to Tkinter, you will be guided step-by-step through the application development process. Over the course of the book, your application will evolve from a simple data-entry form to a complex data management and visualization tool while maintaining a clean and robust design. In addition to building the GUI, you'll learn how to connect to external databases and network resources, test your code to avoid errors, and maximize performance using asynchronous programming. You'll make the most of Tkinter's cross-platform availability by learning how to maintain compatibility, mimic platform-native look and feel, and build executables for deployment across popular computing platforms. By the end of this book, you will have the skills and confidence to design and build powerful high-end GUI applications to solve real-world problems. Style and approach This is a comprehensive guide that explores the essential Tkinter features and modules and implements them in building real-world cross-platform GUI applications Downloading the example code for this book You can download the example code files for all Packt books you have purchased from your account at http://ww...
    Note: Description based on online resource; title from title page (Safari, viewed June 7, 2018)
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  • 92
    Online Resource
    Online Resource
    Birmingham, UK : Packt Publishing
    ISBN: 9781788837149 , 1788837142
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Robotics ; Robots ; Programming ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Leverage the power of Python to build DIY robotic projects About This Book Design, build, and stimulate collaborative robots Build high-end robotics projects such as a customized personal Jarvis Leverage the power of Python and ROS for DIY robotic projects Who This Book Is For If building robots is your dream, then this book is made for you. Prior knowledge of Python would be an added advantage. What You Will Learn Get to know the basics of robotics and its functions Walk through interface components with microcontrollers Integrate robotics with the IoT environment Build projects using machine learning Implement path planning and vision processing Interface your robots with Bluetooth In Detail Robotics is a fast-growing industry. Multiple surveys state that investment in the field has increased tenfold in the last 6 years, and is set to become a $100-billion sector by 2020. Robots are prevalent throughout all industries, and they are all set to be a part of our domestic lives. This book starts with the installation and basic steps in configuring a robotic controller. You'll then move on to setting up your environment to use Python with the robotic controller. You'll dive deep into building simple robotic projects, such as a pet-feeding robot, and more complicated projects, such as machine learning enabled home automation system (Jarvis), vision processing based robots and a self-driven robotic vehicle using Python. By the end of this book, you'll know how to build smart robots using Python. Style and approach A simple step-by-step guide to help you learn the concepts of robotics using simple to advanced steps. You'll not only learn the concepts of AI, machine learning, and Vision Processing, but also how to practically implement them in your projects.
    Note: Description based on online resource; title from title page (Safari, viewed June 20, 2018)
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  • 93
    ISBN: 9781788624534 , 178862453X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Artificial intelligence ; Machine learning ; Python (Computer program language) ; Neural networks (Computer science) ; Electronic books ; Electronic books ; local
    Abstract: A comprehensive guide to advanced deep learning techniques, including Autoencoders, GANs, VAEs, and Deep Reinforcement Learning, that drive today's most impressive AI results Key Features Explore the most advanced deep learning techniques that drive modern AI results Implement Deep Neural Networks, Autoencoders, GANs, VAEs, and Deep Reinforcement Learning A wide study of GANs, including Improved GANs, Cross-Domain GANs and Disentangled Representation GANs Book Description Recent developments in deep learning, including GANs, Variational Autoencoders, and Deep Reinforcement Learning, are creating impressive AI results in our news headlines - such as AlphaGo Zero beating world chess champions, and generative AI that can create art paintings that sell for over $400k because they are so human-like. Advanced Deep Learning with Keras is a comprehensive guide to the advanced deep learning techniques available today, so you can create your own cutting-edge AI. Using Keras as an open-source deep learning library, you'll find hands-on projects throughout that show you how to create more effective AI with the latest techniques. The journey begins with an overview of MLPs, CNNs, and RNNs, which are the building blocks for the more advanced techniques in the book. You'll learn how to implement deep learning models with Keras and Tensorflow, and move forwards to advanced techniques, as you explore deep neural network architectures, including ResNet and DenseNet, and how to create Autoencoders. You then learn all about Generative Adversarial Networks (GANs), and how they can open new levels of AI performance. Variational AutoEncoders (VAEs) are implemented, and you'll see how GANs and VAEs have the generative power to synthesize data that can be extremely convincing to humans - a major stride forward for modern AI. To complete this set of advanced techniques, you'll learn how to implement Deep Reinforcement Learning (DRL) such as Deep Q-Learning and Policy Gradient Methods, which are critical to many modern results in AI. What you will learn Cutting-edge techniques in human-like AI performance Implement advanced deep learning models using Keras The building blocks for advanced techniques - MLPs, CNNs, and RNNs Deep neural networks ? ResNet and DenseNet Autoencoders and Variational AutoEncoders (VAEs) Generative Adversarial Networks (GANs) and creative AI techniques Disentangled Representation GANs, and Cross-Domain GANs Deep Reinforcement Learning (DRL) meth...
    Note: "Expert insight.". - Includes bibliographical references and index. - Description based on online resource; title from cover (Safari, viewed December 10, 2018)
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  • 94
    ISBN: 9781787283220 , 1787283224
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Medical care ; Data processing ; Machine learning ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Add a touch of data analytics to your healthcare systems and get insightful outcomes Key Features Perform healthcare analytics with Python and SQL Build predictive models on real healthcare data with pandas and scikit-learn Use analytics to improve healthcare performance Book Description In recent years, machine learning technologies and analytics have been widely utilized across the healthcare sector. Healthcare Analytics Made Simple bridges the gap between practising doctors and data scientists. It equips the data scientists' work with healthcare data and allows them to gain better insight from this data in order to improve healthcare outcomes. This book is a complete overview of machine learning for healthcare analytics, briefly describing the current healthcare landscape, machine learning algorithms, and Python and SQL programming languages. The step-by-step instructions teach you how to obtain real healthcare data and perform descriptive, predictive, and prescriptive analytics using popular Python packages such as pandas and scikit-learn. The latest research results in disease detection and healthcare image analysis are reviewed. By the end of this book, you will understand how to use Python for healthcare data analysis, how to import, collect, clean, and refine data from electronic health record (EHR) surveys, and how to make predictive models with this data through real-world algorithms and code examples. What you will learn Gain valuable insight into healthcare incentives, finances, and legislation Discover the connection between machine learning and healthcare processes Use SQL and Python to analyze data Measure healthcare quality and provider performance Identify features and attributes to build successful healthcare models Build predictive models using real-world healthcare data Become an expert in predictive modeling with structured clinical data See what lies ahead for healthcare analytics Who this book is for Healthcare Analytics Made Simple is for you if you are a developer who has a working knowledge of Python or a related programming language, although you are new to healthcare or predictive modeling with healthcare data. Clinicians interested in analytics and healthcare computing will also benefit from this book. This book can also serve as a textbook for students enrolled in an introductory course on machine learning for healthcare.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed August 27, 2018)
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  • 95
    ISBN: 9781788622578 , 178862257X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    Keywords: Graphical user interfaces (Computer systems) Programming ; Web applications Development ; Python (Computer program language)
    Note: Description based on online resource; title from title page (Safari, viewed May 24, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 96
    ISBN: 9781788398893 , 1788398890
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    Keywords: Python (Computer program language) ; Machine learning
    Note: Description based on online resource; title from cover (Safari, viewed June 5, 2018). - Includes index
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 97
    ISBN: 9781787281134 , 1787281132
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Parallel Title: Erscheint auch als
    RVK:
    Keywords: Application software Development ; Web applications ; Python (Computer program language)
    Note: Description based on online resource; title from title page (Safari, viewed May 21, 2018)
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 98
    ISBN: 9781789617078 , 1789617073
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Third edition.
    Keywords: Python (Computer program language) ; Object-oriented programming (Computer science) ; Electronic books ; Electronic books ; local
    Abstract: Uncover modern Python with this guide to Python data structures, design patterns, and effective object-oriented techniques Key Features In-depth analysis of many common object-oriented design patterns that are more suitable to Python's unique style Learn the latest Python syntax and libraries Explore abstract design patterns and implement them in Python 3.8 Book Description Object-oriented programming (OOP) is a popular design paradigm in which data and behaviors are encapsulated in such a way that they can be manipulated together. This third edition of Python 3 Object-Oriented Programming fully explains classes, data encapsulation, and exceptions with an emphasis on when you can use each principle to develop well-designed software. Starting with a detailed analysis of object-oriented programming, you will use the Python programming language to clearly grasp key concepts from the object-oriented paradigm. You will learn how to create maintainable applications by studying higher level design patterns. The book will show you the complexities of string and file manipulation, and how Python distinguishes between binary and textual data. Not one, but two very powerful automated testing systems, unittest and pytest, will be introduced in this book. You'll get a comprehensive introduction to Python's concurrent programming ecosystem. By the end of the book, you will have thoroughly learned object-oriented principles using Python syntax and be able to create robust and reliable programs confidently. What you will learn Implement objects in Python by creating classes and defining methods Grasp common concurrency techniques and pitfalls in Python 3 Extend class functionality using inheritance Understand when to use object-oriented features, and more importantly when not to use them Discover what design patterns are and why they are different in Python Uncover the simplicity of unit testing and why it's so important in Python Explore concurrent object-oriented programming Who this book is for If you're new to object-oriented programming techniques, or if you have basic Python skills and wish to learn in depth how and when to correctly apply OOP in Python, this is the book for you. If you are an object-oriented programmer for other languages or seeking a leg up in the new world of Python 3.8, you too will find this book a useful introduction to Python. Previous experience with Python 3 is not necessary.
    Note: Description based on online resource; title from title page (viewed January 8, 2019)
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  • 99
    ISBN: 9781789539738 , 1789539730
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Neural networks (Computer science) ; Machine learning ; Python (Computer program language) ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Introduction to deep learning and PyTorch by building a convolutional neural network and recurrent neural network for real-world use cases such as image classification, transfer learning, and natural language processing. Key Features Clear and concise explanations Gives important insights into deep learning models Practical demonstration of key concepts Book Description PyTorch is extremely powerful and yet easy to learn. It provides advanced features, such as supporting multiprocessor, distributed, and parallel computation. This book is an excellent entry point for those wanting to explore deep learning with PyTorch to harness its power. This book will introduce you to the PyTorch deep learning library and teach you how to train deep learning models without any hassle. We will set up the deep learning environment using PyTorch, and then train and deploy different types of deep learning models, such as CNN, RNN, and autoencoders. You will learn how to optimize models by tuning hyperparameters and how to use PyTorch in multiprocessor and distributed environments. We will discuss long short-term memory network (LSTMs) and build a language model to predict text. By the end of this book, you will be familiar with PyTorch's capabilities and be able to utilize the library to train your neural networks with relative ease. What you will learn Set up the deep learning environment using the PyTorch library Learn to build a deep learning model for image classification Use a convolutional neural network for transfer learning Understand to use PyTorch for natural language processing Use a recurrent neural network to classify text Understand how to optimize PyTorch in multiprocessor and distributed environments Train, optimize, and deploy your neural networks for maximum accuracy and performance Learn to deploy production-ready models Who this book is for Developers and Data Scientist familiar with Machine Learning but new to deep learning, or existing practitioners of deep learning who would like to use PyTorch to train their deep learning models will find this book to be useful. Having knowledge of Python programming will be an added advantage, while previous exposure to PyTorch is not needed.
    Note: Description based on online resource; title from title page (viewed February 15, 2019)
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  • 100
    ISBN: 9781789345933 , 1789345936
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Robots ; Programming ; Robots ; Control systems ; Raspberry Pi (Computer) ; Python (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Gain experience of building a next-generation collaboration robot Key Features Get up and running with the fundamentals of robotic programming Program a robot using Python and the Raspberry Pi 3 Learn to build a smart robot with interactive and AI-enabled behaviors Book Description We live in an age where the most difficult human tasks are now automated. Smart and intelligent robots, which will perform different tasks precisely and efficiently, are the requirement of the hour. A combination of Raspberry Pi and Python works perfectly when making these kinds of robots. Learn Robotics Programming starts by introducing you to the basic structure of a robot, along with how to plan, build, and program it. As you make your way through the book, you will gradually progress to adding different outputs and sensors, learning new building skills, and writing code for interesting behaviors with sensors. You'll also be able to update your robot, and set up web, phone, and Wi-Fi connectivity in order to control it. By the end of the book, you will have built a clever robot that can perform basic artificial intelligence (AI) operations. What you will learn Configure a Raspberry Pi for use in a robot Interface motors and sensors with a Raspberry Pi Implement code to make interesting and intelligent robot behaviors Understand the first steps in AI behavior such as speech recognition visual processing Control AI robots using Wi-Fi Plan the budget for requirements of robots while choosing parts Who this book is for Learn Robotics Programming is for programmers, developers, and enthusiasts interested in robotics and developing a fully functional robot. No major experience required just some programming knowledge would be sufficient.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed January 25, 2019)
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