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  • 2015-2019  (333)
  • 1935-1939
  • Birmingham, UK : Packt Publishing  (168)
  • Cham : Springer International Publishing  (165)
  • Machine learning  (168)
  • Human Geography  (165)
Material
Language
Years
Year
  • 1
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783030032074 , 3030032078
    Language: English
    Pages: 1 Online-Ressource (XXVIII, 326 Seiten) , 30 illus., 28 illus. in color.
    Edition: 1st ed. 2019
    Parallel Title: Erscheint auch als Yigitcanlar, Tan Geographies of Disruption
    DDC: 304.2
    Keywords: Human geography ; Regional economics ; Spatial economics ; Economic geography ; Human Geography ; Regional and Spatial Economics ; Economic Geography
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  • 2
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783030009526 , 3030009521
    Language: English
    Pages: 1 Online-Ressource (XXI, 372 Seiten) , 104 illus., 4 illus. in color.
    Edition: 1st ed. 2019
    Series Statement: Advances in Asian Human-Environmental Research
    Parallel Title: Erscheint auch als Lata, Suman Irrigation Water Management for Agricultural Development in Uttar Pradesh, India
    DDC: 304.2
    Keywords: Human geography ; Cultural geography ; Water ; Hydrology ; Agriculture ; Economic geography ; Pollution ; Social and Cultural Geography ; Water ; Agriculture ; Economic Geography ; Pollution ; Human Geography
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  • 3
    ISBN: 9783030059613 , 3030059618
    Language: English
    Pages: 1 Online-Ressource (XXXI, 371 Seiten) , 67 illus., 17 illus. in color.
    Edition: 1st ed. 2019
    Series Statement: Geographies of Tourism and Global Change
    Parallel Title: Erscheint auch als Mayer, Marius Cross-Border Tourism in Protected Areas
    DDC: 304.2
    Keywords: Human geography ; Economic geography ; Tourism ; Management ; Conservation biology ; Ecology  ; Human Geography ; Economic Geography ; Tourism Management ; Conservation Biology
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  • 4
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783319966700 , 3319966707
    Language: English
    Pages: 1 Online-Ressource (XX, 271 Seiten) , 44 illus., 31 illus. in color.
    Edition: 1st ed. 2019
    Series Statement: Springer Climate
    Parallel Title: Erscheint auch als Meyer-Ohlendorf, Lutz Drivers of Climate Change in Urban India
    DDC: 304.2
    Keywords: Sustainability ; Climatology ; Social structure ; Equality ; Human geography ; Sustainability ; Climate Sciences ; Social Structure ; Human Geography
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  • 5
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783030050870 , 3030050874
    Language: English
    Pages: 1 Online-Ressource (XIV, 266 Seiten) , 34 illus., 20 illus. in color.
    Edition: 1st ed. 2019
    Parallel Title: Erscheint auch als Dobeson, Alexander Revaluing Coastal Fisheries
    DDC: 304.2
    Keywords: Human geography ; Economic sociology ; Economic geography ; Cultural geography ; Environmental management ; Human Geography ; Economic Sociology ; Economic Geography ; Social and Cultural Geography ; Environmental Management
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  • 6
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783030116026 , 3030116026
    Language: English
    Pages: 1 Online-Ressource (XXI, 177 Seiten) , 17 illus., 16 illus. in color.
    Edition: 1st ed. 2019
    Series Statement: Springer Geography
    Parallel Title: Erscheint auch als Moinuddin, Shekh The Political Twittersphere in India
    DDC: 304.2
    Keywords: Human geography ; Cultural geography ; Communication in politics ; Communication ; Mass media ; Social and Cultural Geography ; Political Communication ; Media and Communication ; Human Geography ; Media Sociology
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  • 7
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783030050429 , 3030050424
    Language: English
    Pages: 1 Online-Ressource (XIX, 292 Seiten) , 25 illus., 22 illus. in color.
    Edition: 1st ed. 2019
    Parallel Title: Erscheint auch als Integrating Gender into Transport Planning
    DDC: 304.2
    RVK:
    Keywords: Verkehrsplanung ; Stadtgestaltung ; Geschlechterforschung ; Human geography ; Transportation engineering ; Traffic engineering ; Sex ; Sociology, Urban ; Human Geography ; Transportation Technology and Traffic Engineering ; Gender Studies ; Urban Sociology ; Aufsatzsammlung
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  • 8
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783030043933 , 3030043932
    Language: English
    Pages: 1 Online-Ressource (XVIII, 312 Seiten) , 72 illus., 34 illus. in color.
    Edition: 1st ed. 2019
    Series Statement: Perspectives on Geographical Marginality 4
    Parallel Title: Erscheint auch als Rural Areas Between Regional Needs and Global Challenges
    DDC: 304.2
    Keywords: Human geography ; Human Geography
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  • 9
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783030053604 , 3030053601
    Language: English
    Pages: 1 Online-Ressource (XXIII, 412 Seiten) , 267 illus., 256 illus. in color.
    Edition: 1st ed. 2019
    Parallel Title: Erscheint auch als Galan, Juanjo Sectoral Plans and Pilot Projects for Sustainable Development
    DDC: 304.2
    Keywords: Human geography ; Sustainability ; Landscape ecology ; Human Geography ; Sustainability ; Landscape Ecology
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  • 10
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783319517049 , 331951704X
    Language: English
    Pages: 1 Online-Ressource (XLII, 436 Seiten) , 570 illus., 169 illus. in color.
    Edition: 1st ed. 2019
    Parallel Title: Erscheint auch als Ahamer, Gilbert Mapping Global Dynamics
    DDC: 304.2
    Keywords: Sustainability ; Climatology ; Economic geography ; Human geography ; Globalization ; Renewable energy sources ; Sustainability ; Climate Sciences ; Economic Geography ; Human Geography ; Globalization ; Renewable Energy
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  • 11
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783319991450 , 3319991450
    Language: English
    Pages: 1 Online-Ressource (IX, 284 Seiten) , 9 illus., 4 illus. in color.
    Edition: 1st ed. 2019
    Parallel Title: Erscheint auch als Mitchell, Robert E Human Geographies Within the Pale of Settlement
    DDC: 304.2
    Keywords: Human geography ; Sociology, Urban ; Emigration and immigration ; Human Geography ; Urban Sociology ; Human Migration
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  • 12
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer
    ISBN: 9783319734002
    Language: English
    DDC: 304.2
    RVK:
    Keywords: Human Geography ; Linguistics, general ; Geography, general ; Human Geography ; Geography ; Anthropogeografie ; Linguistik ; Linguistik ; Anthropogeografie
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 13
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer
    ISBN: 9783319734002
    Language: English
    DDC: 304.2
    RVK:
    Keywords: Human Geography ; Linguistics, general ; Geography, general ; Human Geography ; Geography ; Anthropogeografie ; Linguistik ; Linguistik ; Anthropogeografie
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 14
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer
    ISBN: 9783319734002
    Language: English
    DDC: 304.2
    RVK:
    Keywords: Human Geography ; Linguistics, general ; Geography, general ; Human Geography ; Geography ; Anthropogeografie ; Linguistik ; Linguistik ; Anthropogeografie
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 15
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Palgrave Macmillan
    ISBN: 9783030050429
    Language: English
    Pages: 1 Online-Ressource (XIX, 292 p. 25 illus., 22 illus. in color)
    Parallel Title: Erscheint auch als
    Parallel Title: Erscheint auch als
    DDC: 304.2
    Keywords: Human Geography ; Transportation Technology and Traffic Engineering ; Gender Studies ; Landscape/Regional and Urban Planning ; Urban Studies/Sociology ; Human Geography ; Traffic Engineering ; Sociology ; Regional planning ; Sociology, Urban ; Stadtgestaltung ; Verkehrsplanung ; Geschlechterforschung ; Verkehrsplanung ; Stadtgestaltung ; Geschlechterforschung
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 16
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783319908786 , 3319908782
    Language: English
    Pages: 1 Online-Ressource (XVI, 205 Seiten) , 29 illus.
    Edition: 1st ed. 2019
    Parallel Title: Erscheint auch als Pleger, Lyn Ellen Democratic Acceptance of Spatial Planning Policy Measures
    DDC: 304.2
    Keywords: Human geography ; Political science ; Environmental policy ; Human Geography ; Political Science ; Environmental Policy
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  • 17
    ISBN: 9783319760780 , 3319760785
    Language: English
    Pages: 1 Online-Ressource (XVII, 574 Seiten) , 94 illus., 50 illus. in color.
    Edition: 1st ed. 2019
    Series Statement: MARE Publication Series 19
    Parallel Title: Erscheint auch als Viability and Sustainability of Small-Scale Fisheries in Latin America and The Caribbean
    DDC: 304.2
    Keywords: Sustainability ; Environmental sciences Social aspects ; Economic geography ; Human geography ; Animal culture ; Human rights ; Sustainability ; Environmental Social Sciences ; Economic Geography ; Human Geography ; Animal Science ; Human Rights
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  • 18
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783319924441 , 3319924443
    Language: English
    Pages: 1 Online-Ressource (XXI, 285 Seiten) , 53 illus., 49 illus. in color.
    Edition: 1st ed. 2019
    Parallel Title: Erscheint auch als Ageing and the Built Environment in Singapore
    DDC: 304.2
    Keywords: Human geography ; Aging ; Community psychology ; Human Geography ; Ageing ; Community Psychology
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  • 19
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783319924984 , 3319924982
    Language: English
    Pages: 1 Online-Ressource (XIV, 228 Seiten) , 76 illus., 59 illus. in color.
    Edition: 1st ed. 2019
    Series Statement: Sustainable Development Goals Series
    Parallel Title: Erscheint auch als Resettlement Challenges for Displaced Populations and Refugees
    DDC: 304.8
    Keywords: Migration ; Nachhaltigkeit ; Wirtschaftsentwicklung ; Umsiedlung ; Vertreibung ; Emigration and immigration ; Sustainability ; Economic development ; Human geography ; Climatology ; Human Migration ; Sustainability ; Development Studies ; Human Geography ; Climate Sciences
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  • 20
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783319768403 , 3319768409
    Language: English
    Pages: 1 Online-Ressource (XX, 208 Seiten) , 45 illus., 37 illus. in color.
    Edition: 1st ed. 2019
    Parallel Title: Erscheint auch als Van Duzer, Chet Henricus Martellus’s World Map at Yale (c. 1491)
    DDC: 304.2
    Keywords: Human geography ; Geographic information systems ; Africa History ; Cultural property ; Digital humanities ; Lasers ; Human Geography ; Geographical Information System ; African History ; Cultural Heritage ; Digital Humanities ; Laser
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  • 21
    ISBN: 9783319936628 , 331993662X
    Language: English
    Pages: 1 Online-Ressource (XV, 259 Seiten) , 50 illus., 28 illus. in color.
    Edition: 1st ed. 2019
    Series Statement: The Urban Book Series
    Parallel Title: Erscheint auch als Eastern Mediterranean Port Cities
    DDC: 304.2
    Keywords: Human geography ; Cities and towns History ; Middle East History ; Sustainability ; Sociology, Urban ; Urban economics ; Human Geography ; Urban History ; History of the Middle East ; Sustainability ; Urban Sociology ; Urban Economics
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  • 22
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783319897400 , 3319897403
    Language: English
    Pages: 1 Online-Ressource (XVII, 331 Seiten) , 5 illus., 4 illus. in color.
    Edition: 1st ed. 2019
    Parallel Title: Erscheint auch als Ecologically Unequal Exchange
    DDC: 304.2
    Keywords: Environmental sciences Social aspects ; Human geography ; Physical geography ; Ecology  ; Globalization ; Environmental Social Sciences ; Human Geography ; Physical Geography ; Ecology ; Globalization
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  • 23
    ISBN: 9783319940243 , 3319940244
    Language: English
    Pages: 1 Online-Ressource (XXIII, 161 Seiten) , 23 illus., 22 illus. in color.
    Edition: 1st ed. 2019
    Parallel Title: Erscheint auch als Miklós, László Landscape as a Geosystem
    DDC: 304.2
    Keywords: Human geography ; Landscape ecology ; Geographic information systems ; Physical geography ; Human Geography ; Landscape Ecology ; Geographical Information System ; Earth System Sciences
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  • 24
    ISBN: 9783030009700 , 303000970X
    Language: English
    Pages: 1 Online-Ressource (VI, 58 Seiten) , 20 illus., 19 illus. in color.
    Edition: 1st ed. 2019
    Series Statement: SpringerBriefs in Geography
    Parallel Title: Erscheint auch als Pohjola, Jari Historical Perspectives to Postglacial Uplift
    DDC: 304.2
    Keywords: Human geography ; Archaeology ; Geology ; Geographic information systems ; Europe History ; Geotechnical engineering ; Human Geography ; Archaeology ; Geology ; Geographical Information System ; European History ; Geotechnical Engineering and Applied Earth Sciences
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  • 25
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783319969954 , 3319969951
    Language: English
    Pages: 1 Online-Ressource (XXIII, 249 Seiten) , 15 illus., 13 illus. in color.
    Edition: 1st ed. 2019
    Parallel Title: Erscheint auch als Wassenhoven, Louis C The Ancestry of Regional Spatial Planning
    DDC: 304.2
    Keywords: Human geography ; Cities and towns History ; Regionalism ; History, Modern ; Human Geography ; Urban History ; Regionalism ; Modern History
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  • 26
    ISBN: 9783030005849 , 3030005844
    Language: English
    Pages: 1 Online-Ressource (XVIII, 383 Seiten) , 31 illus., 14 illus. in color.
    Edition: 1st ed. 2019
    Parallel Title: Erscheint auch als Contextualizing Health and Aging in the Americas
    DDC: 571,878
    Keywords: Aging ; Public health ; Population Economic aspects ; Human geography ; Ageing ; Public Health ; Population Economics ; Human Geography
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  • 27
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783319778754 , 3319778757
    Language: English
    Pages: 1 Online-Ressource (XVIII, 273 Seiten) , 130 illus., 85 illus. in color.
    Edition: 1st ed. 2019
    Parallel Title: Erscheint auch als New Cities and Community Extensions in Egypt and the Middle East
    DDC: 304.2
    Keywords: Human geography ; Urban economics ; Sociology, Urban ; Sustainability ; Human Geography ; Urban Economics ; Urban Sociology ; Sustainability
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  • 28
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783319966526 , 3319966529
    Language: English
    Pages: 1 Online-Ressource (XVIII, 233 Seiten) , 1 illus.
    Edition: 1st ed. 2019
    Parallel Title: Erscheint auch als Jetzkowitz, Jens Co-Evolution of Nature and Society
    DDC: 304.2
    Keywords: Environmental sciences Social aspects ; Environment ; Human geography ; Sustainability ; Environmental Social Sciences ; Environmental Sciences ; Human Geography ; Sustainability
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  • 29
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783319955766 , 3319955764
    Language: English
    Pages: 1 Online-Ressource (VIII, 270 Seiten) , 31 illus., 24 illus. in color.
    Edition: 1st ed. 2019
    Series Statement: GeoJournal Library 124
    Parallel Title: Erscheint auch als Agrourbanism
    DDC: 304.2
    Keywords: Human geography ; Agriculture ; Biotic communities ; Human Geography ; Agriculture ; Ecosystems
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  • 30
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783319921891 , 3319921894
    Language: English
    Pages: 1 Online-Ressource (XVII, 264 Seiten) , 8 illus.
    Edition: 1st ed. 2019
    Parallel Title: Erscheint auch als Social Practices and Dynamic Non-Humans
    DDC: 304.2
    Keywords: Human geography ; Environmental sciences Social aspects ; Science Social aspects ; Social sciences Philosophy ; User interfaces (Computer systems) ; Human-computer interaction ; Human Geography ; Environmental Social Sciences ; Science and Technology Studies ; Social Theory ; User Interfaces and Human Computer Interaction
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  • 31
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783319980355 , 3319980351
    Language: English
    Pages: 1 Online-Ressource (XVI, 252 Seiten) , 53 illus., 49 illus. in color.
    Edition: 1st ed. 2019
    Series Statement: Historical Geography and Geosciences
    Parallel Title: Erscheint auch als Stogiannos, Alexandros The Genesis of Geopolitics and Friedrich Ratzel
    DDC: 304.2
    Keywords: Human geography ; World politics ; Plants Evolution ; International relations ; Ethnology ; Europe History ; Human Geography ; Political History ; Plant Evolution ; International Relations ; Ethnography ; European History
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  • 32
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783030020118 , 3030020118
    Language: English
    Pages: 1 Online-Ressource (XXXIII, 302 Seiten) , 54 illus., 10 illus. in color.
    Edition: 1st ed. 2019
    Series Statement: The Urban Book Series
    Parallel Title: Erscheint auch als Acheampong, Ransford A Spatial Planning in Ghana
    DDC: 304.2
    Keywords: Human geography ; Political planning ; Sustainability ; Economic development ; Human Geography ; Public Policy ; Sustainability ; Development Studies
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  • 33
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783319919508 , 3319919504
    Language: English
    Pages: 1 Online-Ressource (XIII, 228 Seiten) , 123 illus., 117 illus. in color.
    Edition: 1st ed. 2019
    Series Statement: Contemporary Urban Design Thinking
    Parallel Title: Erscheint auch als Contemporary Urban Design Thinking
    DDC: 304.2
    Keywords: Human geography ; Climatology ; Sustainability ; Buildings Design and construction ; Environmental sciences Social aspects ; Human Geography ; Climate Sciences ; Sustainability ; Building Construction and Design ; Environmental Social Sciences
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  • 34
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783319964393 , 3319964399
    Language: English
    Pages: 1 Online-Ressource (XXI, 106 Seiten) , 3 illus., 2 illus. in color.
    Edition: 1st ed. 2019
    Series Statement: Palgrave Studies in Disaster Anthropology
    Parallel Title: Erscheint auch als Carter, Lyn Indigenous Pacific Approaches to Climate Change
    DDC: 305.8
    Keywords: Ethnology ; Environmental sciences Social aspects ; Environmental policy ; Human geography ; Sociocultural Anthropology ; Environmental Social Sciences ; Environmental Policy ; Human Geography
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  • 35
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783319778877 , 3319778870
    Language: English
    Pages: 1 Online-Ressource (XXIV, 226 Seiten) , 44 illus., 34 illus. in color.
    Edition: 1st ed. 2019
    Series Statement: The Urban Book Series
    Parallel Title: Erscheint auch als Pasini, Roberto Landscape Paradigms and Post-urban Spaces
    DDC: 304.2
    Keywords: Human geography ; Landscape ecology ; Human Geography ; Landscape Ecology
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  • 36
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783319953519 , 3319953516
    Language: English
    Pages: 1 Online-Ressource (VI, 238 Seiten) , 64 illus., 30 illus. in color.
    Edition: 1st ed. 2019
    Series Statement: Human Dynamics in Smart Cities
    Parallel Title: Erscheint auch als Cities as Spatial and Social Networks
    DDC: 304.2
    Keywords: Human geography ; Sociology, Urban ; Human Geography ; Urban Sociology
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  • 37
    ISBN: 9781788471770 , 1788471776
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Machine learning ; Information visualization ; Electronic data processing ; Distributed processing ; Open source software ; Electronic books ; Electronic books ; local
    Abstract: Leverage Elastic Stack's machine learning features to gain valuable insight from your data Key Features Combine machine learning with the analytic capabilities of Elastic Stack Analyze large volumes of search data and gain actionable insight from them Use external analytical tools with your Elastic Stack to improve its performance Book Description Machine Learning with the Elastic Stack is a comprehensive overview of the embedded commercial features of anomaly detection and forecasting. The book starts with installing and setting up Elastic Stack. You will perform time series analysis on varied kinds of data, such as log files, network flows, application metrics, and financial data. As you progress through the chapters, you will deploy machine learning within the Elastic Stack for logging, security, and metrics. In the concluding chapters, you will see how machine learning jobs can be automatically distributed and managed across the Elasticsearch cluster and made resilient to failure. By the end of this book, you will understand the performance aspects of incorporating machine learning within the Elastic ecosystem and create anomaly detection jobs and view results from Kibana directly. What you will learn Install the Elastic Stack to use machine learning features Understand how Elastic machine learning is used to detect a variety of anomaly types Apply effective anomaly detection to IT operations and security analytics Leverage the output of Elastic machine learning in custom views, dashboards, and proactive alerting Combine your created jobs to correlate anomalies of different layers of infrastructure Learn various tips and tricks to get the most out of Elastic machine learning Who this book is for If you are a data professional eager to gain insight on Elasticsearch data without having to rely on a machine learning specialist or custom development, Machine Learning with the Elastic Stack is for you. Those looking to integrate machine learning within their search and analytics applications will also find this book very useful. Prior experience with the Elastic Stack is needed to get the most out of this book.
    Note: Description based on online resource; title from title page (Safari, viewed March 22, 2019)
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  • 38
    ISBN: 9781788999700 , 1788999703
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Spark (Electronic resource : Apache Software Foundation) ; Machine learning ; Electronic data processing ; Distributed processing ; Information visualization ; Electronic books ; Electronic books ; local
    Abstract: Speed up the design and implementation of deep learning solutions using Apache Spark Key Features Explore the world of distributed deep learning with Apache Spark Train neural networks with deep learning libraries such as BigDL and TensorFlow Develop Spark deep learning applications to intelligently handle large and complex datasets Book Description Deep learning is a subset of machine learning where datasets with several layers of complexity can be processed. Hands-On Deep Learning with Apache Spark addresses the sheer complexity of technical and analytical parts and the speed at which deep learning solutions can be implemented on Apache Spark. The book starts with the fundamentals of Apache Spark and deep learning. You will set up Spark for deep learning, learn principles of distributed modeling, and understand different types of neural nets. You will then implement deep learning models, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) on Spark. As you progress through the book, you will gain hands-on experience of what it takes to understand the complex datasets you are dealing with. During the course of this book, you will use popular deep learning frameworks, such as TensorFlow, Deeplearning4j, and Keras to train your distributed models. By the end of this book, you'll have gained experience with the implementation of your models on a variety of use cases. What you will learn Understand the basics of deep learning Set up Apache Spark for deep learning Understand the principles of distribution modeling and different types of neural networks Obtain an understanding of deep learning algorithms Discover textual analysis and deep learning with Spark Use popular deep learning frameworks, such as Deeplearning4j, TensorFlow, and Keras Explore popular deep learning algorithms Who this book is for If you are a Scala developer, data scientist, or data analyst who wants to learn how to use Spark for implementing efficient deep learning models, Hands-On Deep Learning with Apache Spark is for you. Knowledge of the core machine learning concepts and some exposure to Spark will be helpful.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 25, 2019)
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  • 39
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783319922829 , 3319922823
    Language: English
    Pages: 1 Online-Ressource (XIV, 189 Seiten) , 17 illus., 16 illus. in color.
    Edition: 1st ed. 2019
    Parallel Title: Erscheint auch als Relocation of Economic Activity
    DDC: 304.2
    Keywords: Human geography ; Economic geography ; International economic integration ; Globalization ; Regionalism ; Physical geography ; Business logistics ; Human Geography ; Economic Geography ; Emerging Markets and Globalization ; Regionalism ; Physical Geography ; Supply Chain Management
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  • 40
    Online Resource
    Online Resource
    Birmingham, UK : Packt Publishing
    ISBN: 9781789951462 , 1789951461
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: R (Computer program language) ; Machine learning ; Data mining ; Electronic books ; Electronic books ; local
    Abstract: Design clever algorithms that discover hidden patterns and draw responses from unstructured, unlabeled data. Key Features Build state-of-the-art algorithms that can solve your business' problems Learn how to find hidden patterns in your data Revise key concepts with hands-on exercises using real-world datasets Book Description Starting with the basics, Applied Unsupervised Learning with R explains clustering methods, distribution analysis, data encoders, and features of R that enable you to understand your data better and get answers to your most pressing business questions. This book begins with the most important and commonly used method for unsupervised learning - clustering - and explains the three main clustering algorithms - k-means, divisive, and agglomerative. Following this, you'll study market basket analysis, kernel density estimation, principal component analysis, and anomaly detection. You'll be introduced to these methods using code written in R, with further instructions on how to work with, edit, and improve R code. To help you gain a practical understanding, the book also features useful tips on applying these methods to real business problems, including market segmentation and fraud detection. By working through interesting activities, you'll explore data encoders and latent variable models. By the end of this book, you will have a better understanding of different anomaly detection methods, such as outlier detection, Mahalanobis distances, and contextual and collective anomaly detection. What you will learn Implement clustering methods such as k-means, agglomerative, and divisive Write code in R to analyze market segmentation and consumer behavior Estimate distribution and probabilities of different outcomes Implement dimension reduction using principal component analysis Apply anomaly detection methods to identify fraud Design algorithms with R and learn how to edit or improve code Who this book is for Applied Unsupervised Learning with R is designed for business professionals who want to learn about methods to understand their data better, and developers who have an interest in unsupervised learning. Although the book is for beginners, it will be beneficial to have some basic, beginner-level familiarity with R. This includes an understanding of how to open the R console, how to read data, and how to create a loop. To easily understand the concepts of this book, you should also know basic mathematical concepts, including ex...
    Note: Includes bibliographical references. - Description based on online resource; title from copyright page (Safari, viewed May 15, 2019)
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  • 41
    ISBN: 9781789803198 , 1789803195
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Microsoft Cognitive Toolkit ; Neural networks (Computer science) ; Machine learning ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Learn how to train popular deep learning architectures such as autoencoders, convolutional and recurrent neural networks while discovering how you can use deep learning models in your software applications with Microsoft Cognitive Toolkit Key Features Understand the fundamentals of Microsoft Cognitive Toolkit and set up the development environment Train different types of neural networks using Cognitive Toolkit and deploy it to production Evaluate the performance of your models and improve your deep learning skills Book Description Cognitive Toolkit is a very popular and recently open sourced deep learning toolkit by Microsoft. Cognitive Toolkit is used to train fast and effective deep learning models. This book will be a quick introduction to using Cognitive Toolkit and will teach you how to train and validate different types of neural networks, such as convolutional and recurrent neural networks. This book will help you understand the basics of deep learning. You will learn how to use Microsoft Cognitive Toolkit to build deep learning models and discover what makes this framework unique so that you know when to use it. This book will be a quick, no-nonsense introduction to the library and will teach you how to train different types of neural networks, such as convolutional neural networks, recurrent neural networks, autoencoders, and more, using Cognitive Toolkit. Then we will look at two scenarios in which deep learning can be used to enhance human capabilities. The book will also demonstrate how to evaluate your models' performance to ensure it trains and runs smoothly and gives you the most accurate results. Finally, you will get a short overview of how Cognitive Toolkit fits in to a DevOps environment What you will learn Set up your deep learning environment for the Cognitive Toolkit on Windows and Linux Pre-process and feed your data into neural networks Use neural networks to make effcient predictions and recommendations Train and deploy effcient neural networks such as CNN and RNN Detect problems in your neural network using TensorBoard Integrate Cognitive Toolkit with Azure ML Services for effective deep learning Who this book is for Data Scientists, Machine learning developers, AI developers who wish to train and deploy effective deep learning models using Microsoft CNTK will find this book to be useful. Readers need to have experience in Python or similar object-oriented language like C# or Java.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed May 8, 2019)
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  • 42
    ISBN: 9781789536966 , 1789536960
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: TensorFlow ; Application software ; Development ; Neural networks (Computer science) ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Perform supervised and unsupervised machine learning and learn advanced techniques such as training neural networks. Key Features Train your own models for effective prediction, using high-level Keras API Perform supervised and unsupervised machine learning and learn advanced techniques such as training neural networks Get acquainted with some new practices introduced in TensorFlow 2.0 Alpha Book Description TensorFlow is one of the most popular machine learning frameworks in Python. With this book, you will improve your knowledge of some of the latest TensorFlow features and will be able to perform supervised and unsupervised machine learning and also train neural networks. After giving you an overview of what's new in TensorFlow 2.0 Alpha, the book moves on to setting up your machine learning environment using the TensorFlow library. You will perform popular supervised machine learning tasks using techniques such as linear regression, logistic regression, and clustering. You will get familiar with unsupervised learning for autoencoder applications. The book will also show you how to train effective neural networks using straightforward examples in a variety of different domains. By the end of the book, you will have been exposed to a large variety of machine learning and neural network TensorFlow techniques. What you will learn Use tf.Keras for fast prototyping, building, and training deep learning neural network models Easily convert your TensorFlow 1.12 applications to TensorFlow 2.0-compatible files Use TensorFlow to tackle traditional supervised and unsupervised machine learning applications Understand image recognition techniques using TensorFlow Perform neural style transfer for image hybridization using a neural network Code a recurrent neural network in TensorFlow to perform text-style generation Who this book is for Data scientists, machine learning developers, and deep learning enthusiasts looking to quickly get started with TensorFlow 2 will find this book useful. Some Python programming experience with version 3.6 or later, along with a familiarity with Jupyter notebooks will be an added advantage. Exposure to machine learning and neural network techniques would also be helpful.
    Note: Description based on online resource; title from title page (Safari, viewed May 1, 2019)
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  • 43
    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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  • 44
    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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  • 45
    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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  • 46
    ISBN: 9781789134193 , 1789134196
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Machine learning ; Neural networks (Computer science) ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Explore various Generative Adversarial Network architectures using the Python ecosystem Key Features Use different datasets to build advanced projects in the Generative Adversarial Network domain Implement projects ranging from generating 3D shapes to a face aging application Explore the power of GANs to contribute in open source research and projects Book Description Generative Adversarial Networks (GANs) have the potential to build next-generation models, as they can mimic any distribution of data. Major research and development work is being undertaken in this field since it is one of the rapidly growing areas of machine learning. This book will test unsupervised techniques for training neural networks as you build seven end-to-end projects in the GAN domain. Generative Adversarial Network Projects begins by covering the concepts, tools, and libraries that you will use to build efficient projects. You will also use a variety of datasets for the different projects covered in the book. The level of complexity of the operations required increases with every chapter, helping you get to grips with using GANs. You will cover popular approaches such as 3D-GAN, DCGAN, StackGAN, and CycleGAN, and you'll gain an understanding of the architecture and functioning of generative models through their practical implementation. By the end of this book, you will be ready to build, train, and optimize your own end-to-end GAN models at work or in your own projects. What you will learn Train a network on the 3D ShapeNet dataset to generate realistic shapes Generate anime characters using the Keras implementation of DCGAN Implement an SRGAN network to generate high-resolution images Train Age-cGAN on Wiki-Cropped images to improve face verification Use Conditional GANs for image-to-image translation Understand the generator and discriminator implementations of StackGAN in Keras Who this book is for If you're a data scientist, machine learning developer, deep learning practitioner, or AI enthusiast looking for a project guide to test your knowledge and expertise in building real-world GANs models, this book is for you.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 25, 2019)
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  • 47
    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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  • 48
    ISBN: 9781789806090 , 1789806097
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Machine learning ; R (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Master a range of machine learning domains with real-world projects using TensorFlow for R, H2O, MXNet, and more Key Features Master machine learning, deep learning, and predictive modeling concepts in R 3.5 Build intelligent end-to-end projects for finance, retail, social media, and a variety of domains Implement smart cognitive models with helpful tips and best practices Book Description R is one of the most popular languages when it comes to performing computational statistics (statistical computing) easily and exploring the mathematical side of machine learning. With this book, you will leverage the R ecosystem to build efficient machine learning applications that carry out intelligent tasks within your organization. This book will help you test your knowledge and skills, guiding you on how to build easily through to complex machine learning projects. You will first learn how to build powerful machine learning models with ensembles to predict employee attrition. Next, you'll implement a joke recommendation engine and learn how to perform sentiment analysis on Amazon reviews. You'll also explore different clustering techniques to segment customers using wholesale data. In addition to this, the book will get you acquainted with credit card fraud detection using autoencoders, and reinforcement learning to make predictions and win on a casino slot machine. By the end of the book, you will be equipped to confidently perform complex tasks to build research and commercial projects for automated operations. What you will learn Explore deep neural networks and various frameworks that can be used in R Develop a joke recommendation engine to recommend jokes that match users' tastes Create powerful ML models with ensembles to predict employee attrition Build autoencoders for credit card fraud detection Work with image recognition and convolutional neural networks Make predictions for casino slot machine using reinforcement learning Implement NLP techniques for sentiment analysis and customer segmentation Who this book is for If you're a data analyst, data scientist, or machine learning developer who wants to master machine learning concepts using R by building real-world projects, this is the book for you. Each project will help you test your skills in implementing machine learning algorithms and techniques. A basic understanding of machine learning and working knowledge of R programming is necessary to get the most out of this book.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 6, 2019)
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  • 49
    ISBN: 9781838552138 , 1838552138
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Neural networks (Computer science) ; Java (Computer program language) ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Leverage the power of Java and deep learning to build production-grade Computer Vision applications Key Features Build real-world Computer Vision applications using the power of neural networks Implement image classification, object detection, and face recognition Know best practices on effectively building and deploying deep learning models in Java Book Description Although machine learning is an exciting world to explore, you may feel confused by all of its theoretical aspects. As a Java developer, you will be used to telling the computer exactly what to do, instead of being shown how data is generated; this causes many developers to struggle to adapt to machine learning. The goal of this book is to walk you through the process of efficiently training machine learning and deep learning models for Computer Vision using the most up-to-date techniques. The course is designed to familiarize you with neural networks, enabling you to train them efficiently, customize existing state-of-the-art architectures, build real-world Java applications, and get great results in a short space of time. You will build real-world Computer Vision applications, ranging from a simple Java handwritten digit recognition model to real-time Java autonomous car driving systems and face recognition models. By the end of this book, you will have mastered the best practices and modern techniques needed to build advanced Computer Vision Java applications and achieve production-grade accuracy. What you will learn Discover neural Networks and their applications in Computer Vision Explore the popular Java frameworks and libraries for deep learning Build deep neural networks in Java Implement an end-to-end image classification application in Java Perform real-time video object detection using deep learning Enhance performance and deploy applications for production Who this book is for This book is for data scientists, machine learning developers and deep learning practitioners with Java knowledge who want to implement machine learning and deep neural networks in the computer vision domain. You will need to have a basic knowledge of Java programming.
    Note: Description based on online resource; title from title page (Safari, viewed April 2, 2019)
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  • 50
    ISBN: 9781789347043 , 1789347041
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Mobile apps ; Application software ; Development ; Artificial intelligence ; Machine learning ; Mobile computing ; Electronic books ; Electronic books ; local
    Abstract: Learn to build end-to-end AI apps from scratch for Android and iOS using TensorFlow Lite, CoreML, and PyTorch Key Features Build practical, real-world AI projects on Android and iOS Implement tasks such as recognizing handwritten digits, sentiment analysis, and more Explore the core functions of machine learning, deep learning, and mobile vision Book Description We're witnessing a revolution in Artificial Intelligence, thanks to breakthroughs in deep learning. Mobile Artificial Intelligence Projects empowers you to take part in this revolution by applying Artificial Intelligence (AI) techniques to design applications for natural language processing (NLP), robotics, and computer vision. This book teaches you to harness the power of AI in mobile applications along with learning the core functions of NLP, neural networks, deep learning, and mobile vision. It features a range of projects, covering tasks such as real-estate price prediction, recognizing hand-written digits, predicting car damage, and sentiment analysis. You will learn to utilize NLP and machine learning algorithms to make applications more predictive, proactive, and capable of making autonomous decisions with less human input. In the concluding chapters, you will work with popular libraries, such as TensorFlow Lite, CoreML, and PyTorch across Android and iOS platforms. By the end of this book, you will have developed exciting and more intuitive mobile applications that deliver a customized and more personalized experience to users. What you will learn Explore the concepts and fundamentals of AI, deep learning, and neural networks Implement use cases for machine vision and natural language processing Build an ML model to predict car damage using TensorFlow Deploy TensorFlow on mobile to convert speech to text Implement GAN to recognize hand-written digits Develop end-to-end mobile applications that use AI principles Work with popular libraries, such as TensorFlow Lite, CoreML, and PyTorch Who this book is for Mobile Artificial Intelligence Projects is for machine learning professionals, deep learning engineers, AI engineers, and software engineers who want to integrate AI technology into mobile-based platforms and applications. Sound knowledge of machine learning and experience with any programming language is all you need to get started with this book.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed May 14, 2019)
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  • 51
    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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  • 52
    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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  • 53
    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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  • 54
    ISBN: 9781789533347 , 1789533341
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Machine learning ; Neural networks (Computer science) ; Artificial intelligence ; Electronic books ; Electronic books ; local
    Abstract: Your one-stop guide to learning and implementing artificial neural networks with Keras effectively Key Features Design and create neural network architectures on different domains using Keras Integrate neural network models in your applications using this highly practical guide Get ready for the future of neural networks through transfer learning and predicting multi network models Book Description Neural networks are used to solve a wide range of problems in different areas of AI and deep learning. Hands-On Neural Networks with Keras will start with teaching you about the core concepts of neural networks. You will delve into combining different neural network models and work with real-world use cases, including computer vision, natural language understanding, synthetic data generation, and many more. Moving on, you will become well versed with convolutional neural networks (CNNs), recurrent neural networks (RNNs), long short-term memory (LSTM) networks, autoencoders, and generative adversarial networks (GANs) using real-world training datasets. We will examine how to use CNNs for image recognition, how to use reinforcement learning agents, and many more. We will dive into the specific architectures of various networks and then implement each of them in a hands-on manner using industry-grade frameworks. By the end of this book, you will be highly familiar with all prominent deep learning models and frameworks, and the options you have when applying deep learning to real-world scenarios and embedding artificial intelligence as the core fabric of your organization. What you will learn Understand the fundamental nature and workflow of predictive data modeling Explore how different types of visual and linguistic signals are processed by neural networks Dive into the mathematical and statistical ideas behind how networks learn from data Design and implement various neural networks such as CNNs, LSTMs, and GANs Use different architectures to tackle cognitive tasks and embed intelligence in systems Learn how to generate synthetic data and use augmentation strategies to improve your models Stay on top of the latest academic and commercial developments in the field of AI Who this book is for This book is for machine learning practitioners, deep learning researchers and AI enthusiasts who are looking to get well versed with different neural network architecture using Keras. Working knowledge of Python programming language is mandatory.
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed May 14, 2019)
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  • 55
    ISBN: 9781789613568 , 1789613566
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Edition: Third edition.
    Keywords: Machine learning ; R (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Stay updated with expert techniques for solving data analytics and machine learning challenges and gain insights from complex projects and power up your applications Key Features Build independent machine learning (ML) systems leveraging the best features of R 3.5 Understand and apply different machine learning techniques using real-world examples Use methods such as multi-class classification, regression, and clustering Book Description Given the growing popularity of the R-zerocost statistical programming environment, there has never been a better time to start applying ML to your data. This book will teach you advanced techniques in ML ,using? the latest code in R 3.5. You will delve into various complex features of supervised learning, unsupervised learning, and reinforcement learning algorithms to design efficient and powerful ML models. This newly updated edition is packed with fresh examples covering a range of tasks from different domains. Mastering Machine Learning with R starts by showing you how to quickly manipulate data and prepare it for analysis. You will explore simple and complex models and understand how to compare them. You'll also learn to use the latest library support, such as TensorFlow and Keras-R, for performing advanced computations. Additionally, you'll explore complex topics, such as natural language processing (NLP), time series analysis, and clustering, which will further refine your skills in developing applications. Each chapter will help you implement advanced ML algorithms using real-world examples. You'll even be introduced to reinforcement learning, along with its various use cases and models. In the concluding chapters, you'll get a glimpse into how some of these blackbox models can be diagnosed and understood. By the end of this book, you'll be equipped with the skills to deploy ML techniques in your own projects or at work. What you will learn Prepare data for machine learning methods with ease Understand how to write production-ready code and package it for use Produce simple and effective data visualizations for improved insights Master advanced methods, such as Boosted Trees and deep neural networks Use natural language processing to extract insights in relation to text Implement tree-based classifiers, including Random Forest and Boosted Tree Who this book is for This book is for data science professionals, machine learning engineers, or anyone who is looking for the ideal guide to help them implement...
    Note: Previous edition published: 2017. - Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 25, 2019)
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  • 56
    ISBN: 9781788998765 , 1788998766
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Reinforcement learning ; Machine learning ; Computer games ; Programming ; Neural networks (Computer science) ; Application software ; Development ; Electronic books ; Electronic books ; local
    Abstract: Understand the core concepts of deep learning and deep reinforcement learning by applying them to develop games Key Features Apply the power of deep learning to complex reasoning tasks by building a Game AI Exploit the most recent developments in machine learning and AI for building smart games Implement deep learning models and neural networks with Python Book Description The number of applications of deep learning and neural networks has multiplied in the last couple of years. Neural nets has enabled significant breakthroughs in everything from computer vision, voice generation, voice recognition and self-driving cars. Game development is also a key area where these techniques are being applied. This book will give an in depth view of the potential of deep learning and neural networks in game development. We will take a look at the foundations of multi-layer perceptron's to using convolutional and recurrent networks. In applications from GANs that create music or textures to self-driving cars and chatbots. Then we introduce deep reinforcement learning through the multi-armed bandit problem and other OpenAI Gym environments. As we progress through the book we will gain insights about DRL techniques such as Motivated Reinforcement Learning with Curiosity and Curriculum Learning. We also take a closer look at deep reinforcement learning and in particular the Unity ML-Agents toolkit. By the end of the book, we will look at how to apply DRL and the ML-Agents toolkit to enhance, test and automate your games or simulations. Finally, we will cover your possible next steps and possible areas for future learning. What you will learn Learn the foundations of neural networks and deep learning. Use advanced neural network architectures in applications to create music, textures, self driving cars and chatbots. Understand the basics of reinforcement and DRL and how to apply it to solve a variety of problems. Working with Unity ML-Agents toolkit and how to install, setup and run the kit. Understand core concepts of DRL and the differences between discrete and continuous action environments. Use several advanced forms of learning in various scenarios from developing agents to testing games. Who this book is for This books is for game developers who wish to create highly interactive games by leveraging the power of machine and deep learning. No prior knowledge of machine learning, deep learning or neural networks is required this book will teach those concept...
    Note: Description based on online resource; title from title page (Safari, viewed May 14, 2019)
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  • 57
    ISBN: 9781788832762 , 1788832760
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Internet of things ; Artificial intelligence ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Build smarter systems by combining artificial intelligence and the Internet of Things - two of the most talked about topics today Key Features Leverage the power of Python libraries such as TensorFlow and Keras to work with real-time IoT data Process IoT data and predict outcomes in real time to build smart IoT models Cover practical case studies on industrial IoT, smart cities, and home automation Book Description There are many applications that use data science and analytics to gain insights from terabytes of data. These apps, however, do not address the challenge of continually discovering patterns for IoT data. In Hands-On Artificial Intelligence for IoT, we cover various aspects of artificial intelligence (AI) and its implementation to make your IoT solutions smarter. This book starts by covering the process of gathering and preprocessing IoT data gathered from distributed sources. You will learn different AI techniques such as machine learning, deep learning, reinforcement learning, and natural language processing to build smart IoT systems. You will also leverage the power of AI to handle real-time data coming from wearable devices. As you progress through the book, techniques for building models that work with different kinds of data generated and consumed by IoT devices such as time series, images, and audio will be covered. Useful case studies on four major application areas of IoT solutions are a key focal point of this book. In the concluding chapters, you will leverage the power of widely used Python libraries, TensorFlow and Keras, to build different kinds of smart AI models. By the end of this book, you will be able to build smart AI-powered IoT apps with confidence. What you will learn Apply different AI techniques including machine learning and deep learning using TensorFlow and Keras Access and process data from various distributed sources Perform supervised and unsupervised machine learning for IoT data Implement distributed processing of IoT data over Apache Spark using the MLLib and H2O.ai platforms Forecast time-series data using deep learning methods Implementing AI from case studies in Personal IoT, Industrial IoT, and Smart Cities Gain unique insights from data obtained from wearable devices and smart devices Who this book is for If you are a data science professional or a machine learning developer looking to build smart systems for IoT, Hands-On Artificial Intelligence for IoT is for you. If you want to learn how po...
    Note: Description based on online resource; title from title page (Safari, viewed March 19, 2019)
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  • 58
    ISBN: 9781788831611 , 1788831616
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Machine learning ; Electronic books ; Electronic books ; local
    Abstract: Your hands-on reference guide to developing, training, and optimizing your machine learning models Key Features Your guide to learning efficient machine learning processes from scratch Explore expert techniques and hacks for a variety of machine learning concepts Write effective code in R, Python, Scala, and Spark to solve all your machine learning problems Book Description Machine learning makes it possible to learn about the unknowns and gain hidden insights into your datasets by mastering many tools and techniques. This book guides you to do just that in a very compact manner. After giving a quick overview of what machine learning is all about, Machine Learning Quick Reference jumps right into its core algorithms and demonstrates how they can be applied to real-world scenarios. From model evaluation to optimizing their performance, this book will introduce you to the best practices in machine learning. Furthermore, you will also look at the more advanced aspects such as training neural networks and work with different kinds of data, such as text, time-series, and sequential data. Advanced methods and techniques such as causal inference, deep Gaussian processes, and more are also covered. By the end of this book, you will be able to train fast, accurate machine learning models at your fingertips, which you can easily use as a point of reference. What you will learn Get a quick rundown of model selection, statistical modeling, and cross-validation Choose the best machine learning algorithm to solve your problem Explore kernel learning, neural networks, and time-series analysis Train deep learning models and optimize them for maximum performance Briefly cover Bayesian techniques and sentiment analysis in your NLP solution Implement probabilistic graphical models and causal inferences Measure and optimize the performance of your machine learning models Who this book is for If you're a machine learning practitioner, data scientist, machine learning developer, or engineer, this book will serve as a reference point in building machine learning solutions. You will also find this book useful if you're an intermediate machine learning developer or data scientist looking for a quick, handy reference to all the concepts of machine learning. You'll need some exposure to machine learning to get the best out of this book.
    Note: Description based on online resource; title from title page (Safari, viewed March 19, 2019)
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  • 59
    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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  • 60
    ISBN: 9781789342666 , 178934266X
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Spark (Electronic resource : Apache Software Foundation) ; Electronic data processing ; Distributed processing ; Management ; Big data ; Machine learning ; Electronic books ; Electronic books ; local
    Abstract: A practical guide for solving complex data processing challenges by applying the best optimizations techniques in Apache Spark. Key Features Learn about the core concepts and the latest developments in Apache Spark Master writing efficient big data applications with Spark's built-in modules for SQL, Streaming, Machine Learning and Graph analysis Get introduced to a variety of optimizations based on the actual experience Book Description Apache Spark is a flexible framework that allows processing of batch and real-time data. Its unified engine has made it quite popular for big data use cases. This book will help you to get started with Apache Spark 2.0 and write big data applications for a variety of use cases. It will also introduce you to Apache Spark ? one of the most popular Big Data processing frameworks. Although this book is intended to help you get started with Apache Spark, but it also focuses on explaining the core concepts. This practical guide provides a quick start to the Spark 2.0 architecture and its components. It teaches you how to set up Spark on your local machine. As we move ahead, you will be introduced to resilient distributed datasets (RDDs) and DataFrame APIs, and their corresponding transformations and actions. Then, we move on to the life cycle of a Spark application and learn about the techniques used to debug slow-running applications. You will also go through Spark's built-in modules for SQL, streaming, machine learning, and graph analysis. Finally, the book will lay out the best practices and optimization techniques that are key for writing efficient Spark applications. By the end of this book, you will have a sound fundamental understanding of the Apache Spark framework and you will be able to write and optimize Spark applications. What you will learn Learn core concepts such as RDDs, DataFrames, transformations, and more Set up a Spark development environment Choose the right APIs for your applications Understand Spark's architecture and the execution flow of a Spark application Explore built-in modules for SQL, streaming, ML, and graph analysis Optimize your Spark job for better performance Who this book is for If you are a big data enthusiast and love processing huge amount of data, this book is for you. If you are data engineer and looking for the best optimization techniques for your Spark applications, then you will find this book helpful. This book also helps data scientists who want to implement their mach...
    Note: Includes bibliographical references. - Description based on online resource; title from title page (Safari, viewed March 25, 2019)
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  • 61
    ISBN: 9781789342109 , 1789342104
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Machine learning ; Neural networks (Computer science) ; Electronic books ; Electronic books ; local
    Abstract: Implement neural network architectures by building them from scratch for multiple real-world applications. Key Features From scratch, build multiple neural network architectures such as CNN, RNN, LSTM in Keras Discover tips and tricks for designing a robust neural network to solve real-world problems Graduate from understanding the working details of neural networks and master the art of fine-tuning them Book Description This book will take you from the basics of neural networks to advanced implementations of architectures using a recipe-based approach. We will learn about how neural networks work and the impact of various hyper parameters on a network's accuracy along with leveraging neural networks for structured and unstructured data. Later, we will learn how to classify and detect objects in images. We will also learn to use transfer learning for multiple applications, including a self-driving car using Convolutional Neural Networks. We will generate images while leveraging GANs and also by performing image encoding. Additionally, we will perform text analysis using word vector based techniques. Later, we will use Recurrent Neural Networks and LSTM to implement chatbot and Machine Translation systems. Finally, you will learn about transcribing images, audio, and generating captions and also use Deep Q-learning to build an agent that plays Space Invaders game. By the end of this book, you will have developed the skills to choose and customize multiple neural network architectures for various deep learning problems you might encounter. What you will learn Build multiple advanced neural network architectures from scratch Explore transfer learning to perform object detection and classification Build self-driving car applications using instance and semantic segmentation Understand data encoding for image, text and recommender systems Implement text analysis using sequence-to-sequence learning Leverage a combination of CNN and RNN to perform end-to-end learning Build agents to play games using deep Q-learning Who this book is for This intermediate-level book targets beginners and intermediate-level machine learning practitioners and data scientists who have just started their journey with neural networks. This book is for those who are looking for resources to help them navigate through the various neural network architectures; you'll build multiple architectures, with concomitant case studies ordered by the complexity of the problem. A basic un...
    Note: Description based on online resource; title from title page (Safari, viewed April 18, 2019)
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  • 62
    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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  • 63
    ISBN: 9781838647056 , 1838647058
    Language: English
    Pages: 1 online resource (1 volume) , illustrations
    Keywords: Machine learning ; R (Computer program language) ; Electronic books ; Electronic books ; local
    Abstract: Learn how to use R to apply powerful machine learning methods and gain insight into real-world applications using clustering, logistic regressions, random forests, support vector machine, and more. Key Features Use R 3.5 to implement real-world examples in machine learning Implement key machine learning algorithms to understand the working mechanism of smart models Create end-to-end machine learning pipelines using modern libraries from the R ecosystem Book Description Machine Learning with R Quick Start Guide takes you on a data-driven journey that starts with the very basics of R and machine learning. It gradually builds upon core concepts so you can handle the varied complexities of data and understand each stage of the machine learning pipeline. From data collection to implementing Natural Language Processing (NLP), this book covers it all. You will implement key machine learning algorithms to understand how they are used to build smart models. You will cover tasks such as clustering, logistic regressions, random forests, support vector machines, and more. Furthermore, you will also look at more advanced aspects such as training neural networks and topic modeling. By the end of the book, you will be able to apply the concepts of machine learning, deal with data-related problems, and solve them using the powerful yet simple language that is R. What you will learn Introduce yourself to the basics of machine learning with R 3.5 Get to grips with R techniques for cleaning and preparing your data for analysis and visualize your results Learn to build predictive models with the help of various machine learning techniques Use R to visualize data spread across multiple dimensions and extract useful features Use interactive data analysis with R to get insights into data Implement supervised and unsupervised learning, and NLP using R libraries Who this book is for This book is for graduate students, aspiring data scientists, and data analysts who wish to enter the field of machine learning and are looking to implement machine learning techniques and methodologies from scratch using R 3.5. A working knowledge of the R programming language is expected.
    Note: Description based on online resource; title from title page (Safari, viewed May 9, 2019)
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  • 64
    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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  • 65
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783030113988 , 3030113981
    Language: English
    Pages: 1 Online-Ressource (XVII, 262 Seiten) , 18 illus., 16 illus. in color.
    Edition: 1st ed. 2019
    Series Statement: Key Challenges in Geography, EUROGEO Book Series
    Parallel Title: Erscheint auch als O'Reilly, Gerry Aligning Geopolitics, Humanitarian Action and Geography in Times of Conflict
    DDC: 304.2
    Keywords: Human geography ; Cultural geography ; Peace ; Economic development ; Humanitarian law ; Political science ; Social and Cultural Geography ; Peace and Conflict Studies ; Human Geography ; Development Studies ; International Humanitarian Law, Law of Armed Conflict ; Political Science
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  • 66
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783030148423 , 3030148424
    Language: English
    Pages: 1 Online-Ressource (XXI, 281 Seiten) , 31 illus., 27 illus. in color.
    Edition: 1st ed. 2019
    Series Statement: Palgrave Studies in Natural Resource Management
    Parallel Title: Erscheint auch als Glazier, Edward W Tradition-Based Natural Resource Management
    DDC: 304.2
    Keywords: Environmental sciences Social aspects ; Environmental management ; Energy policy ; Energy and state ; Human geography ; Physical geography ; Environmental Social Sciences ; Environmental Management ; Energy Policy, Economics and Management ; Human Geography ; Physical Geography
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  • 67
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783030060947 , 3030060942
    Language: English
    Pages: 1 Online-Ressource (XX, 235 Seiten) , 94 illus., 89 illus. in color.
    Edition: 1st ed. 2019
    Series Statement: The Urban Book Series
    Parallel Title: Erscheint auch als Suhartini, Ninik Urban Governance and Informal Settlements
    DDC: 304.2
    Keywords: Human geography ; Political science ; Ethnology ; Culture ; Human Geography ; Governance and Government ; Regional Cultural Studies
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  • 68
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783030010751 , 3030010759
    Language: English
    Pages: 1 Online-Ressource (XXIII, 365 Seiten) , 530 illus., 349 illus. in color.
    Edition: 1st ed. 2019
    Parallel Title: Erscheint auch als Folkers, Antoni S Modern Architecture in Africa
    DDC: 304.2
    Keywords: Human geography ; Cultural property ; Buildings Environmental engineering ; Cities and towns History ; Human Geography ; Cultural Heritage ; Building Physics, HVAC ; Urban History
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  • 69
    ISBN: 9783319769448 , 3319769448
    Language: English
    Pages: 1 Online-Ressource (VIII, 304 Seiten) , 83 illus., 42 illus. in color.
    Edition: 1st ed. 2019
    Series Statement: Resilient Cities, Re-thinking Urban Transformation
    Parallel Title: Erscheint auch als Urban Resilience for Risk and Adaptation Governance
    DDC: 304.2
    Keywords: Human geography ; Management ; Environmental management ; Climatology ; Environmental policy ; Human Geography ; Management ; Environmental Management ; Climate Sciences ; Environmental Policy
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  • 70
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783030173128 , 3030173127
    Language: English
    Pages: 1 Online-Ressource (XXII, 337 Seiten)
    Edition: 1st ed. 2019
    Series Statement: Advances in Science, Technology & Innovation, IEREK Interdisciplinary Series for Sustainable Development
    Parallel Title: Erscheint auch als Bibri, Simon Elias Big Data Science and Analytics for Smart Sustainable Urbanism
    DDC: 304.2
    Keywords: Human geography ; Quantitative research ; Sustainability ; Dynamics ; Nonlinear theories ; Technological innovations ; Human Geography ; Data Analysis and Big Data ; Sustainability ; Applied Dynamical Systems ; Innovation and Technology Management
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  • 71
    Online Resource
    Online Resource
    Cham : Springer International Publishing
    ISBN: 9783319974002
    Language: English
    Pages: Online-Ressource (XVIII, 312 p. 3 illus., 2 illus. in color, online resource)
    Edition: Springer eBook Collection. Social Sciences
    Series Statement: Palgrave Studies in Environmental Transformation, Transition and Accountability
    Series Statement: SpringerLink
    Series Statement: Bücher
    Parallel Title: Erscheint auch als Transformative climates and accountable governance
    Parallel Title: Printed edition
    Parallel Title: Printed edition
    RVK:
    RVK:
    Keywords: Environment Studies ; Environment ; Human Geography ; Environment ; Human Geography ; Climate change. ; Environmental geography. ; Climatic changes ; Environmental responsibility ; Klimaänderung ; Klimaschutz ; Internationale Kooperation
    Abstract: ‘Transformative and Accountable Climate Governance describes the paradigmatic influences and frameworks within which transformations and transitions in light of a warming earth will occur. The book thereby pursues a multi-disciplinary angle and offers an impressive interdisciplinary approach with truly international outlook. In its entirety, the book is therefore of direct relevance for academia, practitioners and public policy specialists around the globe.’ - Julia M. Puaschunder, Prize Fellow at the Inter-University Consortium of New York, USA This book explores the real-world consequences changing ideas and strategies have on effective climate governance. Its main focus is on why accountability matters - both for transformations and transitions in international climate change governance and how international support for environmentally responsible actions, and extending shared accountabilities, might strengthen climate governance globally. A main point of discussion is if and how better understanding of accountabilities and transformations in ecosystems dynamics, the capacities of organisms to adapt, migrate or otherwise respond to environmental or climatic changes, can improve climate governance mechanisms. Bringing together a diverse set of considerations from various fields of study, chapters examine responses to environmental transformations that occur during periods of climatic crisis, such as species depletion, industrialisation, de-industrialisation or urbanisation. Throughout, this book aims to further readers understanding of if or how accountable climate governance can reduce the risks of global political disorder and widespread conflict in the 21st century, arising from environmental transformations of depleted forests, re-routed waterways, coastlines impacted by sea level rises, changed rainfall patterns and industrial practices. Beth Edmondson is a senior lecturer in the School of Arts at Federation University Australia. Her research focuses on international responses to global climate change, the possibilities for order in the international political system, the nature of sovereignty and the scope of international law in constructing governmental capacities. Stuart Levy is a senior lecturer in the School of Education at Federation University Australia. His interests in international relations include the nature and evolution of state sovereignty and the politics of global climate change
    Abstract: Chapter 1: Introduction: Transformative Climates and Accountable Governance; Beth Edmondson & Stuart Levy -- Section One: Chapter 2: The Limits of States and Changing Regulatory Frameworks; Beth Edmondson & Stuart Levy -- Chapter 3: Order and Accountability in Governing Transforming Environments; Beth Edmondson & Stuart Levy -- Chapter 4: Climate Governance for Nation States in the Anthropocene - an agenda for transformation in Australia; Josephine Mummery & Jane Mummery -- Chapter 5: The Empire Strikes Back: Fossil Fuel Companies, Investor-State Dispute Settlement, International Trade, and Accountable Governance; Matthew Rimmer -- Chapter 6: The public’s perception of international climate leadership: Insights from the European Union; Jale Tosun, Mile Micic & Nicole Schmidt -- Section Two: Chapter 7: Selected studies in Economic & Environmental Accountabilities; Beth Edmondson & Stuart Levy -- Chapter 8: Allocating the Burdens of Climate Action: Consumption-based Carbon Accounting and the Polluter-pays Principle; Ross Mittiga -- Chapter 9: Comparison of climate change, human and non-human migration governance; Martina Grecequet, Jessica Hellmann, Jack DeWaard & Yudi Li -- Chapter 10: Representing whose access and allocation interests? Stakeholder perceptions and interests representation in climate governance; Timothy Cadman, Tek Maraseni, Hugh Breakey & Hawn Ok Ma -- Chapter 11: Constraining supply: the moral case for limiting fossil fuel exports; Jeremy Moss -- Chapter 12: Personal carbon trading and individual mitigation accountability ; Steven Vanderheiden -- Chapter 13: Conclusion: Where to next? Accountable Governance and Transformative Climates; Beth Edmondson & Stuart Levy
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    Online Resource
    Online Resource
    Cham : Springer International Publishing
    ISBN: 9783319981109
    Language: English
    Pages: Online-Ressource (XV, 289 p, online resource)
    Edition: Springer eBook Collection. Social Sciences
    Series Statement: SpringerLink
    Series Statement: Bücher
    Parallel Title: Erscheint auch als
    Parallel Title: Printed edition
    Parallel Title: Printed edition
    Keywords: Environment Studies ; Environment ; Environmental management ; Human Geography ; Environmental policy ; Environment ; Environmental management ; Human Geography ; Environmental policy ; Environmental geography.
    Abstract: This book provides a critical review of global environmental governance as part of the broader process of sustainably transforming modern society. The author argues for substantial modifications, outlining potential improvements in knowledge bridging processes, integration and synthesis that offer valuable information for environmental policy and governance. These improvements, he argues, should be achieved through the use of theoretical and empirical knowledge gleaned from global scenario analysis and interdisciplinary environmental research, and with the aid of new practices for knowledge sharing, cooperation and collective learning. The analysis presented in the book is based on recent developments in social ecology and the author’s interdisciplinary theory of society-nature interaction (Social-Ecological Transformation: Reconnecting Society and Nature, Palgrave Macmillan, 2016)
    Abstract: Chapter 1. Introduction -- Part I: The global environmental situation -- Chapter 2. Environmental change: Human modification of nature - social and environmental consequences -- Chapter 3. Social change: Social agency and human relations with nature in the industrial society -- Chapter 4. Policy change: Crisis of environmental policy and global governance -- Part II: Knowledge for renewing environmental governance -- Chapter 5. Environmental research and governance: Institutional problems of bridging knowledge divides and communicating science -- Chapter 6. Interdisciplinary knowledge integration for environmental governance: Epistemological questions -- Chapter 7. Social-ecological theory and global environmental governance -- Part III: Towards the future society: World ecology and changing societal relations with nature -- Chapter 8. Global environmental change and the transformation of the earth system -- Chapter 9. Beyond globalisation: Another transformation of the economic world system -- Chapter 10. Rethinking and renewing global environmental governance as part of social-ecological transformation
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  • 73
    Online Resource
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    Cham : Springer International Publishing
    ISBN: 9783319946917
    Language: English
    Pages: Online-Ressource (XV, 113 p, online resource)
    Edition: Springer eBook Collection. Social Sciences
    Series Statement: SpringerLink
    Series Statement: Bücher
    Parallel Title: Erscheint auch als
    Parallel Title: Printed edition
    Parallel Title: Printed edition
    Keywords: Environment Studies ; Environment ; Human Geography ; Environmental policy ; Environment ; Human Geography ; Environmental policy ; Environmental geography. ; Climate change.
    Abstract: ‘The challenge of coping with uncertain climate risks and potential disruption across a range of sectors is a topic that is increasingly coming to the fore… Dr. Howarth and colleagues skilfully set out the nature of the problem, the barriers to responding effectively, and some innovative thinking about the importance of collaboration and communication to improve resilience.’ -Kristen Guida, London Climate Change Partnership, UK ‘Anyone concerned with communication of environmental risks, public understanding of science and risk, and planning for resilient responses to environmental shocks to our systems, will benefit from reading this book and applying its lessons.’ -Dr Ian Christie, University of Surrey, UK The frequency and intensity of climate shocks such as heatwaves and flooding, are expected to increase under a changing climate with severe implications across the food, energy, water, environment nexus. This book critically explores how to improve resilience to climate shocks by examining the range of challenges and opportunities that exist in the aftermath of shocks and discusses factors that exacerbate and mitigate these. It innovatively discusses the importance of embedding communication, collaboration and co-production within resilience-building across sectors and stakeholders. Doing so with policy, practitioner and scientific communities, Candice Howarth argues, can pave the way to overcome challenges that emerge from climate shocks and facilitate the co-design of sustainable, robust and resilient responses
    Abstract: 1. Introduction: nexus shocks -- 2. Exacerbating and mitigating nexus shocks -- 3. Opportunities and challenges emerging from nexus shocks -- 4. The importance of communication, collaboration and co-production -- 5. Looking ahead
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  • 74
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    Cham : Springer International Publishing | Imprint: Palgrave Macmillan
    ISBN: 9783319960623
    Language: English
    Pages: 1 Online-Ressource (XII, 194 p)
    Parallel Title: Printed edition
    Parallel Title: Printed edition
    DDC: 306.48
    RVK:
    RVK:
    Keywords: Sports-Sociological aspects ; Tourism ; Human Geography
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 75
    ISBN: 9783319922829
    Language: English
    Pages: 1 Online-Ressource (XIV, 189 p. 17 illus., 16 illus. in color)
    Parallel Title: Printed edition
    Parallel Title: Printed edition
    DDC: 304.2
    Keywords: Human Geography ; Geography ; Globalization ; Economic development ; Business logistics
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (URL des Erstveröffentlichers)
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    URL: Cover
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  • 76
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    Cham : Springer International Publishing | Imprint: Palgrave Pivot
    ISBN: 9783319964393
    Language: English
    Pages: 1 Online-Ressource (XXI, 106 p. 3 illus., 2 illus. in color)
    Series Statement: Palgrave Studies in Disaster Anthropology
    Parallel Title: Printed edition
    Parallel Title: Printed edition
    DDC: 306
    Keywords: Ethnology ; Environmental sociology ; Environmental policy ; Human Geography
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 77
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    Online Resource
    Cham : Springer International Publishing | Imprint: Palgrave Macmillan
    ISBN: 9783319986968
    Language: English
    Pages: 1 Online-Ressource (XXXVII, 477 p. 64 illus., 33 illus. in color)
    Parallel Title: Printed edition
    Parallel Title: Printed edition
    DDC: 304.2
    RVK:
    Keywords: Human Geography ; Marine Sciences ; Geographical information systems ; Environmental management ; Environmental law ; Aufsatzsammlung ; Aufsatzsammlung ; Aufsatzsammlung ; Aufsatzsammlung
    URL: Volltext  (kostenfrei)
    URL: Volltext  (kostenfrei)
    URL: Volltext  (kostenfrei)
    URL: Volltext  (kostenfrei)
    URL: Volltext  (kostenfrei)
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    URL: Volltext  (kostenfrei)
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  • 78
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Imprint: Springer
    ISBN: 9783030032074
    Language: English
    Pages: 1 Online-Ressource (XXVIII, 326 p. 30 illus., 28 illus. in color)
    Parallel Title: Printed edition
    Parallel Title: Printed edition
    DDC: 304.2
    RVK:
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    Keywords: Human Geography ; Regional planning ; Regional economics ; Geography ; Aufsatzsammlung ; Aufsatzsammlung ; Aufsatzsammlung
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 79
    ISBN: 9783030059613
    Language: English
    Pages: 1 Online-Ressource (XXXI, 371 p. 67 illus., 17 illus. in color)
    Series Statement: Geographies of Tourism and Global Change
    Parallel Title: Printed edition
    Parallel Title: Printed edition
    DDC: 304.2
    RVK:
    RVK:
    Keywords: Human Geography ; Geography ; Tourism ; Nature Conservation
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 80
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Imprint: Palgrave Macmillan
    ISBN: 9783030149802
    Language: English
    Pages: 1 Online-Ressource (XVIII, 300 p. 14 illus., 11 illus. in color)
    Series Statement: Palgrave Studies in Globalization, Culture and Society
    Parallel Title: Printed edition
    Parallel Title: Printed edition
    Parallel Title: Printed edition
    DDC: 306
    Keywords: Culture ; Communication ; Literature    ; Human Geography
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  • 81
    ISBN: 9783319966526
    Language: English
    Pages: Online-Ressource (XVIII, 233 p. 1 illus, online resource)
    Edition: Springer eBook Collection. Social Sciences
    Series Statement: SpringerLink
    Series Statement: Bücher
    Parallel Title: Erscheint auch als
    Parallel Title: Printed edition
    Parallel Title: Printed edition
    Dissertation note: Habilitationsschrift Hamburg, Helmut-Schmidt-Universität, Universität der Bundeswehr 2014
    Keywords: Environmental Sociology ; Environmental sociology ; Environment ; Human Geography ; Sustainable development ; Environmental sociology ; Environment ; Human Geography ; Sustainable development ; Hochschulschrift
    Abstract: This book offers support for interdisciplinary research on the interactions of nature and society. It is based on the hypothesis that a science of coevolution is needed to explore paths to a sustainable future. Jens Jetzkowitz initially discusses why social science knowledge only rarely finds its way into sustainability discourse. One significant issue is a view of science that separates knowing and acting, and the book illustrates current problems in conceptualising interdisciplinary knowledge production. It then goes one step further and introduces a workable alternative concept, taking philosophical pragmatism as a point of departure. Sustainable development goals and transdisciplinarity are currently subject to widespread discussions and Jetzkowitz takes a stance on the debates from the perspective of coevolutionary science. This book will appeal to scholars and students interested in environmental and sustainability discourses and to anyone willing to think outside the box
    Abstract: Part I: What is the problem? -- Part II: Where do we stand? -- Part III: Coevolutionary Science -- Part IV: Perspectives of coevolutionary science in sustainability discourse
    Note: "The book is a condensed and abridged version of my habilitation thesis on social science knowledge for the discourse of sustainability, which I submitted at the Helmut Schmidt University/University of the Bundeswehr Hamburg in April 2014"
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  • 82
    Online Resource
    Online Resource
    Cham : Springer International Publishing
    ISBN: 9783319976730
    Language: English
    Pages: Online-Ressource (XII, 308 p. 22 illus. in color, online resource)
    Edition: Springer eBook Collection. Social Sciences
    Series Statement: SpringerLink
    Series Statement: Bücher
    Parallel Title: Erscheint auch als
    Parallel Title: Printed edition
    Parallel Title: Printed edition
    Keywords: Applied psychology ; Environment Studies ; Environment ; Ethnology ; Human Geography ; Applied psychology ; Environment ; Ethnology ; Human Geography ; Environmental geography. ; Community psychology. ; Environmental psychology.
    Abstract: This book explores how natural landscapes are linked to positive mental wellbeing. While natural landscapes have long been represented and portrayed as transformative, the link to mental wellbeing is an area that researchers are still aiming to comprehend. Accompanying five groups of people to rural Scotland, the author considers individual, external and group motivations for journeying from urban environments, examining in what ways these excursions are personally and socially transformative. Far more than traversing mere physical boundaries, this book illustrates the new challenges, experiences, territories and cultures provided by these excursions, firmly anchored in the Scottish countryside. In doing so, the author questions the extent to which people’s own narratives link to the perception that the outdoors are positively transformative - and what indeed does have the power to influence transformation. Grounded in extensive qualitative research, this contemplative and ethnographic book will be of interest and value to students and scholars of the outdoors and its connection to wellbeing. Rebecca Crowther is a transdisciplinary ethnographic researcher working between, across and beyond disciplines within the arts, humanities and social sciences. Her research interests lie in the phenomenological experience of natural landscapes
    Abstract: Chapter 1 Introduction: The Phenomenon -- Chapter 2 A transdisciplinary ethnography -- Chapter 3 Getting out, Goethe and serendipitous ethnography -- Chapter 4 The Journey, belonging and the self -- Chapter 5 The Liminal Loop -- Chapter 6 Anthropocentrism, agency and the transforming self -- Chapter 7 Conclusion: Performed identities and being a good person
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  • 83
    Online Resource
    Online Resource
    Cham : Springer International Publishing
    ISBN: 9783319985152
    Language: English
    Pages: Online-Ressource (XXI, 366 p. 70 illus, online resource)
    Edition: Springer eBook Collection. Social Sciences
    Series Statement: Palgrave Studies in Water Governance: Policy and Practice
    Series Statement: SpringerLink
    Series Statement: Bücher
    Parallel Title: Erscheint auch als
    Parallel Title: Printed edition
    Parallel Title: Printed edition
    Keywords: Environment Studies ; Environment ; Human Geography ; Environment ; Human Geography ; Environmental geography. ; Environmental management.
    Abstract: Access to water is one of the most pressing global issues of the twenty-first century, particularly when set against the background of a rapidly growing global population. This book provides a cutting-edge, comprehensive overview of the challenges facing water governance and regulatory choices. The recently adopted Sustainable Development Goals set forward an ambitious agenda of providing universal access to good quality water supply and sanitation services within a financially constrained environment: however, the various peculiarities of each country regarding water governance makes it difficult to identify and implement the best practices and benchmarks. Drawing together empirical studies from countries around the world, the editors and contributors combine extensive data to review the individual challenges facing each country, from the supervision of autonomous regulatory bodies to the question of centralization and the influence of local utility companies. This pioneering and practical volume will be of interest and value not only to students and scholars of water governance, but also to practitioners and regulators. Simon Porcher is Associate Professor of Management and vice-director of the Economics of Public-Private Partnership Chair at Sorbonne Business School, IAE Paris, Université Paris I Panthéon-Sorbonne, France. He specialises the study of privatization of water public services in France, the UK and Chile and is expanding his research into China, Germany, the Netherlands and Portugal. Stéphane Saussier is Director of the Water research area at the Florence School of Regulation, Italy, and Professor of Economics and Management at the Sorbonne Business School, France. Specialising in issues of water governance, he regularly contributes to reports for international institutions such as the OECD and the European Parliament
    Abstract: Chapter 1. Spain -- Chapter 2. Italy -- Chapter 3. Portugal -- Chapter 4. France -- Chapter 5. Germany -- Chapter 6. - UK -- Chapter 7. - Latin American Countries -- Chapter 8. - Africa -- Chapter 9. Cee -- Chapter 10. China -- Chapter 11. - USA -- Chapter 12 -- Japan
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  • 84
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Imprint: Springer
    ISBN: 9783319955766
    Language: English
    Pages: 1 Online-Ressource (VIII, 270 p. 31 illus., 24 illus. in color)
    Series Statement: GeoJournal Library 124
    Parallel Title: Printed edition
    Parallel Title: Printed edition
    DDC: 304.2
    RVK:
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    Keywords: Human Geography ; Regional planning ; Agriculture ; Endangered ecosystems ; Aufsatzsammlung ; Aufsatzsammlung
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (URL des Erstveröffentlichers)
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    URL: Cover
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  • 85
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    Cham : Springer International Publishing | Imprint: Palgrave Macmillan
    ISBN: 9783319991450
    Language: English
    Pages: 1 Online-Ressource (IX, 284 p. 9 illus., 4 illus. in color)
    Parallel Title: Printed edition
    Parallel Title: Printed edition
    DDC: 304.2
    RVK:
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    Keywords: Human Geography ; Historical geography ; Sociology, Urban ; Migration
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 86
    ISBN: 9783030043933
    Language: English
    Pages: 1 Online-Ressource (XVIII, 312 p. 72 illus., 34 illus. in color)
    Series Statement: Perspectives on Geographical Marginality 4
    Parallel Title: Printed edition
    Parallel Title: Printed edition
    DDC: 304.2
    Keywords: Human Geography ; Regional planning
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  • 87
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    Cham : Springer International Publishing | Imprint: Springer
    ISBN: 9783030040017
    Language: English
    Pages: 1 Online-Ressource (XIV, 148 p. 60 illus)
    Series Statement: Spatial Demography Book Series 2
    Parallel Title: Printed edition
    Parallel Title: Printed edition
    DDC: 304.6
    Keywords: Demography ; Geographical information systems ; Political science ; Human Geography
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 88
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    Cham : Springer International Publishing | Imprint: Palgrave Macmillan
    ISBN: 9783030050870
    Language: English
    Pages: 1 Online-Ressource (XIV, 266 p. 34 illus., 20 illus. in color)
    Parallel Title: Printed edition
    Parallel Title: Printed edition
    DDC: 304.2
    Keywords: Human Geography ; Geography ; Cultural geography ; Environmental management
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 89
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    Cham : Springer International Publishing | Imprint: Palgrave Macmillan
    ISBN: 9783030050429
    Language: English
    Pages: 1 Online-Ressource (XIX, 292 p. 25 illus., 22 illus. in color)
    Parallel Title: Printed edition
    Parallel Title: Printed edition
    DDC: 304.2
    Keywords: Human Geography ; Traffic Engineering ; Sociology ; Regional planning ; Sociology, Urban
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  • 90
    ISBN: 9783030039073
    Language: English
    Pages: 1 Online-Ressource (XVIII, 937 p. 36 illus)
    Series Statement: American Jewish Year Book 118
    Parallel Title: Printed edition
    Parallel Title: Printed edition
    DDC: 305.8
    Keywords: Ethnicity ; Judaism ; Human Geography
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 91
    ISBN: 9783030119508
    Language: English
    Pages: 1 Online-Ressource (X, 271 p. 42 illus., 34 illus. in color)
    Series Statement: Geographies of Tourism and Global Change
    Parallel Title: Printed edition
    Parallel Title: Printed edition
    Parallel Title: Printed edition
    DDC: 304.2
    RVK:
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    Keywords: Human Geography ; Geography ; Tourism ; Regional economics ; Sustainable development ; Economic policy ; Aufsatzsammlung ; Aufsatzsammlung
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 92
    Online Resource
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    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783319960623 , 3319960628
    Language: English
    Pages: 1 Online-Ressource (XII, 194 Seiten)
    Edition: 1st ed. 2019
    Parallel Title: Erscheint auch als Beames, Simon Adventure and Society
    DDC: 306,483
    Keywords: Sports Sociological aspects ; Tourism ; Management ; Human geography ; Educational sociology ; Sport Sociology ; Tourism Management ; Human Geography ; Sociology of Education
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  • 93
    Online Resource
    Online Resource
    Cham : Springer International Publishing
    ISBN: 9783319779560
    Language: English
    Pages: Online-Ressource (XV, 364 p. 27 illus., 24 illus. in color, online resource)
    Edition: Springer eBook Collection. Political Science and International Studies
    Series Statement: SpringerLink
    Series Statement: Bücher
    Parallel Title: Erscheint auch als
    Parallel Title: Printed edition
    Parallel Title: Erscheint auch als Mapping migration, identity, and space
    RVK:
    Keywords: Political science ; Political Science and International Relations ; Political science ; Political theory ; Comparative politics ; Emigration and immigration ; Human geography ; Political theory ; Comparative politics ; Emigration and immigration ; Human geography ; Citizenship. ; International relations. ; International relations ; Migration ; Citizenship ; Human Geography ; Comparative politics ; Political theory ; Political science ; conflicts over identities and space;migration and identity;cultural geography;place and space;border zones and border crossings;state boundaries and internal boundaries ; Aufsatzsammlung ; Migration ; Grenzüberschreitung ; Identität
    Abstract: This interdisciplinary collection of essays focuses on the ways in which movements of people across natural, political, and cultural boundaries shape identities that are inexorably linked to the geographical space that individuals on the move cross, inhabit, and leave behind. As conflicts over identities and space continue to erupt on a regular basis, this book reads the relationship between migration, identity, and space from a fresh and innovative perspective. Tabea Linhard is Professor of Spanish, Comparative Literature, and International Studies at Washington University in St. Louis, USA. Timothy H. Parsons holds a joint appointment as Professor of African History in the History Department and the African and African American Studies Department at Washington University in St. Louis, USA
    Abstract: 1. Introduction: How Does Migration Take Place? -- 2. Walking to the Northern Mines: Mesoamerican Migration in New Spain -- 3. Big History and the Local Response: Migration and Identity in a European Borderland -- 4. Mapping Museums in New Zealand: The Representation of Place Identity in the Permanent Exhibition at the Puhoi Bohemian Museum -- 5. Moving Barbed Wire: Geographies of Border Crossing during World War II -- 6. Image and Imagination in the Creation of Pakistan -- 7. Jumping Tribal Boundaries: Space, Mobility, and Identity in Kenya -- 8. Movement after Migration: The Cultivation of Transnational Algerian Jewish Networks, 1962-1973 -- 9. Silent Forced Migrations in Twenty-First Century Jerusalem -- 10. Defining Borders on Land and Sea: Italy, the European Union, and Mediterranean Refugees 2011-2015 -- 11. B/Ordering Turbulence beyond Europe: Expert Knowledge in the Management of Human Mobility -- 12. The “Right to the City” in the Landscapes of Servitude and Migration, From the Philippines to the Arabian Gulf, and Back -- 13. The Politics of Space and Identity: Making Place in a Suburban District -- 14. Conclusion: A Geographer’s Perspective on Migration, Identity, and Space
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    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783030040017 , 3030040011
    Language: English
    Pages: 1 Online-Ressource (XIV, 148 Seiten) , 60 illus.
    Edition: 1st ed. 2019
    Series Statement: Spatial Demography Book Series 2
    Parallel Title: Erscheint auch als Darmofal, David Demography, Politics, and Partisan Polarization in the United States, 1828–2016
    DDC: 304.6
    Keywords: Demography ; Population ; Geographic information systems ; Political science ; Human geography ; Population and Demography ; Geographical Information System ; Political Science ; Human Geography
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  • 95
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    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783030163617 , 303016361X
    Language: English
    Pages: 1 Online-Ressource (XVII, 168 Seiten) , 71 illus., 18 illus. in color.
    Edition: 1st ed. 2019
    Series Statement: Historical Geography and Geosciences
    Parallel Title: Erscheint auch als Dodgshon, Robert Farming Communities in the Western Alps, 1500–1914
    DDC: 304.2
    Keywords: Human geography ; Social history ; Economic history ; Physical geography ; Agriculture ; Human Geography ; Social History ; Economic History ; Physical Geography ; Agriculture
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  • 96
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783319941509 , 331994150X
    Language: English
    Pages: 1 Online-Ressource (XVII, 291 Seiten) , 179 illus., 137 illus. in color.
    Edition: 1st ed. 2019
    Series Statement: Urban and Landscape Perspectives 20
    Parallel Title: Erscheint auch als Bianconi, Fabio Landscape Lab
    DDC: 304.2
    Keywords: Human geography ; Cultural property ; Computer simulation ; Computer-aided engineering ; Engineering design ; Human Geography ; Cultural Heritage ; Computer Modelling ; Computer-Aided Engineering (CAD, CAE) and Design ; Engineering Design
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  • 97
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783030057732 , 3030057739
    Language: English
    Pages: 1 Online-Ressource (X, 291 Seiten) , 38 illus., 21 illus. in color.
    Edition: 1st ed. 2019
    Series Statement: The Urban Book Series
    Parallel Title: Erscheint auch als Urban and Regional Planning in Turkey
    DDC: 304.2
    Keywords: Human geography ; Ethnology ; Culture ; Human Geography ; Regional Cultural Studies
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  • 98
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783030039073 , 3030039072
    Language: English
    Pages: 1 Online-Ressource (XVIII, 937 Seiten) , 36 illus.
    Edition: 1st ed. 2019
    Series Statement: American Jewish Year Book 118
    Parallel Title: Erscheint auch als American Jewish Year Book 2018
    DDC: 305.8
    Keywords: Race ; Judaism ; Human geography ; Race and Ethnicity Studies ; Judaism ; Human Geography
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  • 99
    ISBN: 9783030119508 , 3030119505
    Language: English
    Pages: 1 Online-Ressource (X, 271 Seiten) , 42 illus., 34 illus. in color.
    Edition: 1st ed. 2019
    Series Statement: Geographies of Tourism and Global Change
    Parallel Title: Erscheint auch als Perspectives on Rural Tourism Geographies
    DDC: 304.2
    Keywords: Human geography ; Economic geography ; Tourism ; Management ; Regional economics ; Spatial economics ; Sustainability ; Economic policy ; Human Geography ; Economic Geography ; Tourism Management ; Regional and Spatial Economics ; Sustainability ; Economic Policy
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  • 100
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer International Publishing AG
    ISBN: 9783030170943 , 3030170942
    Language: English
    Pages: 1 Online-Ressource (X, 231 Seiten) , 12 illus.
    Edition: 1st ed. 2019
    Series Statement: Palgrave Macmillan Studies in Family and Intimate Life
    Parallel Title: Erscheint auch als Hall, Sarah Marie Everyday Life in Austerity
    DDC: 305.2
    Keywords: Sociology ; Social groups ; Social structure ; Equality ; Human geography ; Sociology of Family, Youth and Aging ; Social Structure ; Human Geography
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (URL des Erstveröffentlichers)
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