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  • MPI Ethno. Forsch.  (1,736)
  • Data mining
  • Python (Computer program language)
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Material
Language
Years
Keywords
  • 1
    Online Resource
    Online Resource
    San Francisco, CA : No Starch Press
    ISBN: 9781718503137 , 171850313X
    Language: English
    Pages: 1 online resource
    Parallel Title: Erscheint auch als
    DDC: 005.8/3
    Keywords: Quantitative research Data processing ; Journalism Data processing ; Data mining ; Hacking ; Recherche quantitative ; Informatique ; Journalisme ; Informatique ; Exploration de données (Informatique) ; Piratage informatique
    Abstract: "Covers how to secure and authenticate datasets and safely communicate with sources; Python programming basics for data science investigations; security concepts, like disk encryption; how to work with data in EML, MBOX, JSON, CSV, and SQL formats; and tricks for using the command-line interface to explore datasets packed with secrets"--
    Note: Includes index. - Description based on print version record and CIP data provided by publisher; resource not viewed
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Online Resource
    Online Resource
    [Sebastopol, California] : O'Reilly Media, Inc.
    ISBN: 9781098171568 , 109817156X
    Language: English
    Pages: 1 online resource (5 pages)
    Edition: [First edition].
    Series Statement: Shortcuts
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Python (Langage de programmation)
    Abstract: Build your knowledge of Python, the world's favorite programming language, with this Shortcuts collection. These recipes address a range of well-known and more advanced function definitions, as well as common programming patterns for class and object definitions.
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    Online Resource
    Online Resource
    [Sebastopol, California] : O'Reilly Media, Inc.
    ISBN: 9781098171322 , 1098171322
    Language: English
    Pages: 1 online resource (5 pages)
    Edition: [First edition].
    Series Statement: Shortcuts
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Python (Langage de programmation)
    Abstract: Build your knowledge of Python with this Shortcuts collection. Focusing on common problems involving text manipulation, many of these tasks can be solved using built-in methods of strings. More complicated operations may require regular expressions or the creation of a full-fledged parser.
    Library Location Call Number Volume/Issue/Year Availability
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  • 4
    Online Resource
    Online Resource
    Hoboken, New Jersey : Wiley
    ISBN: 9781394213269 , 1394213263 , 9781394213252 , 1394213255 , 9781394213276 , 1394213271 , 9781394213245
    Language: English
    Pages: 1 online resource
    Parallel Title: Erscheint auch als
    DDC: 006.3/12
    Keywords: Data mining ; R (Computer program language) ; Python (Computer program language) ; Exploration de données (Informatique) ; R (Langage de programmation) ; Python (Langage de programmation)
    Abstract: "Data science is an interdisciplinary academic field that uses statistics, scientific computing, scientific methods, processes, algorithms and systems to extract or extrapolate knowledge and insights from noisy, structured, and unstructured data."--
    Note: Includes index. - Description based on print version record and CIP data provided by publisher; resource not viewed
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  • 5
    Online Resource
    Online Resource
    [Sebastopol, California] : O'Reilly Media, Inc.
    ISBN: 9781098171520 , 1098171527
    Language: English
    Pages: 1 online resource (5 pages)
    Edition: [First edition].
    Series Statement: Shortcuts
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Python (Langage de programmation)
    Abstract: Build your knowledge of Python, the world's favorite programming language, with this Shortcuts collection. These recipes address a range of well-known and more advanced function definitions, as well as common programming patterns for class and object definitions.
    Library Location Call Number Volume/Issue/Year Availability
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  • 6
    Online Resource
    Online Resource
    [Sebastopol, California] : O'Reilly Media, Inc.
    ISBN: 9781098171537 , 1098171535
    Language: English
    Pages: 1 online resource (5 pages)
    Edition: [First edition].
    Series Statement: Shortcuts
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Python (Langage de programmation)
    Abstract: Build your knowledge of Python, the world's favorite programming language, with this Shortcuts collection. These recipes address a range of well-known and more advanced function definitions, as well as common programming patterns for class and object definitions.
    Library Location Call Number Volume/Issue/Year Availability
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  • 7
    Online Resource
    Online Resource
    [Sebastopol, California] : O'Reilly Media, Inc.
    ISBN: 9781098171544 , 1098171543
    Language: English
    Pages: 1 online resource (5 pages)
    Edition: [First edition].
    Series Statement: Shortcuts
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Python (Langage de programmation)
    Abstract: Build your knowledge of Python, the world's favorite programming language, with this Shortcuts collection. These recipes address a range of well-known and more advanced function definitions, as well as common programming patterns for class and object definitions.
    Library Location Call Number Volume/Issue/Year Availability
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  • 8
    Online Resource
    Online Resource
    [Sebastopol, California] : O'Reilly Media, Inc.
    ISBN: 9781098171551 , 1098171551
    Language: English
    Pages: 1 online resource (5 pages)
    Edition: [First edition].
    Series Statement: Shortcuts
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Python (Langage de programmation)
    Abstract: Build your knowledge of Python, the world's favorite programming language, with this Shortcuts collection. These recipes address a range of well-known and more advanced function definitions, as well as common programming patterns for class and object definitions.
    Library Location Call Number Volume/Issue/Year Availability
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  • 9
    Online Resource
    Online Resource
    [Sebastopol, California] : O'Reilly Media, Inc.
    ISBN: 9781098171339 , 1098171330
    Language: English
    Pages: 1 online resource (5 pages)
    Edition: [First edition].
    Series Statement: Shortcuts
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Python (Langage de programmation)
    Abstract: Build your knowledge of Python with this Shortcuts collection. Focusing on common problems involving text manipulation, many of these tasks can be solved using built-in methods of strings. More complicated operations may require regular expressions or the creation of a full-fledged parser.
    Library Location Call Number Volume/Issue/Year Availability
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  • 10
    Online Resource
    Online Resource
    [Place of publication not identified] : O'Reilly Media, Inc.
    Language: English
    Pages: 1 online resource (1 video file (2 hr., 56 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.7
    Keywords: Electronic data processing ; Software engineering ; Big data ; Python (Computer program language) ; Computer programming ; Cloud computing ; Génie logiciel ; Python (Langage de programmation) ; Programmation (Informatique) ; computer programming ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: The systems of today are exponentially more complex than the systems of 15, or even 10 years ago. There are way more moving parts and interactions to keep track of, sometimes leading to systems behaving in very unpredictable ways. In the past, Software Engineers and Site Reliability Engineers (SREs) could rely on logging and monitoring to make sense of their systems. This is no longer the case. The good news is that Observability can help. In this course, you will learn about how Observability can help SREs and Software Engineers make sense of what's going on in their systems. You will also learn about OpenTelemetry: what it is, how it supports Observability goals, how OpenTelemetry instrumentation works, and how the OpenTelemetry Collector and OpenTelemetry Operator further enhance OpenTelemetry's capabilities. You will put OpenTelemetry theory into practice with hands-on exercises which include instrumenting a Python application with OpenTelemetry, configuring the OpenTelemetry Collector, and deploying and configuring the OpenTelemetry Kubernetes Operator. Finally, you will learn what pitfalls to avoid when setting up an Observability practice, to ensure that you and your teams are positioned for success, and explore some advanced Observability use cases supported by OpenTelemetry. What you'll learn and how you can apply it Understand what Observability is, and why it is an important practice for SREs and software engineers Understand how OpenTelemetry helps to achieve Observability, and understand the basic building blocks required to instrument an application Understand the value of the OpenTelemetry Collector, and how to configure and deploy it Understand the value of the OpenTelemetry Operator, and how to configure and deploy it Quickly see OpenTelemetry in action in a complex ecosystem by running the OpenTelemetry Demo App Use OpenTelemetry to instrument a simple Python application and send traces to an Observability back-end via the OpenTelemetry Collector Understand what pitfalls to avoid in order to run a successful Observability practice Understand additional ways in which OpenTelemetry can help achieve Observability This course is for you because... You're a Site Reliability Engineer looking to improve the reliability of your systems. You're a Software Engineer looking to improve the debuggability of your code. Prerequisites: Familiarity with Linux Working knowledge of Python programming Docker fundamentals Git fundamentals Kubernetes fundamentals, including deploying applications to Kubernetes.
    Note: Online resource; title from title details screen (O'Reilly, viewed April 2, 2024)
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  • 11
    Online Resource
    Online Resource
    [Sebastopol, California] : O'Reilly Media, Inc.
    ISBN: 9781098171315 , 1098171314
    Language: English
    Pages: 1 online resource (5 pages)
    Edition: [First edition].
    Series Statement: Shortcuts
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Python (Langage de programmation)
    Abstract: Build your knowledge of Python with this Shortcuts collection. Focusing on common problems involving text manipulation, many of these tasks can be solved using built-in methods of strings. More complicated operations may require regular expressions or the creation of a full-fledged parser.
    Library Location Call Number Volume/Issue/Year Availability
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  • 12
    ISBN: 9781835462683 , 1835462685 , 9781835464946
    Language: English
    Pages: 1 online resource
    Edition: 1st edition.
    Parallel Title: Erscheint auch als
    DDC: 005.13/3
    Keywords: Machine learning ; Python (Computer program language) ; Data mining ; Apprentissage automatique ; Python (Langage de programmation) ; Exploration de données (Informatique)
    Abstract: Use active machine learning with Python to improve the accuracy of predictive models, streamline the data analysis process, and adapt to evolving data trends, fostering innovation and progress across diverse fields Key Features Learn how to implement a pipeline for optimal model creation from large datasets and at lower costs Gain profound insights within your data while achieving greater efficiency and speed Apply your knowledge to real-world use cases and solve complex ML problems Purchase of the print or Kindle book includes a free PDF eBook Book Description Building accurate machine learning models requires quality data--lots of it. However, for most teams, assembling massive datasets is time-consuming, expensive, or downright impossible. Led by Margaux Masson-Forsythe, a seasoned ML engineer and advocate for surgical data science and climate AI advancements, this hands-on guide to active machine learning demonstrates how to train robust models with just a fraction of the data using Python's powerful active learning tools. You'll master the fundamental techniques of active learning, such as membership query synthesis, stream-based sampling, and pool-based sampling and gain insights for designing and implementing active learning algorithms with query strategy and Human-in-the-Loop frameworks. Exploring various active machine learning techniques, you'll learn how to enhance the performance of computer vision models like image classification, object detection, and semantic segmentation and delve into a machine AL method for selecting the most informative frames for labeling large videos, addressing duplicated data. You'll also assess the effectiveness and efficiency of active machine learning systems through performance evaluation. By the end of the book, you'll be able to enhance your active learning projects by leveraging Python libraries, frameworks, and commonly used tools. What you will learn Master the fundamentals of active machine learning Understand query strategies for optimal model training with minimal data Tackle class imbalance, concept drift, and other data challenges Evaluate and analyze active learning model performance Integrate active learning libraries into workflows effectively Optimize workflows for human labelers Explore the finest active learning tools available today Who this book is for Ideal for data scientists and ML engineers aiming to maximize model performance while minimizing costly data labeling, this book is your guide to optimizing ML workflows and prioritizing quality over quantity. Whether you're a technical practitioner or team lead, you'll benefit from the proven methods presented in this book to slash data requirements and iterate faster. Basic Python proficiency and familiarity with machine learning concepts such as datasets and convolutional neural networks is all you need to get started.
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  • 13
    ISBN: 9781805122739 , 1805122738 , 9781805129233
    Language: English
    Pages: 1 online resource
    Edition: 1st edition.
    Parallel Title: Erscheint auch als
    DDC: 519.5/5
    Keywords: Time-series analysis Data processing ; Deep learning (Machine learning) ; Python (Computer program language) ; Série chronologique ; Informatique ; Apprentissage profond ; Python (Langage de programmation)
    Abstract: Learn how to deal with time series data and how to model it using deep learning and take your skills to the next level by mastering PyTorch using different Python recipes Key Features Learn the fundamentals of time series analysis and how to model time series data using deep learning Explore the world of deep learning with PyTorch and build advanced deep neural networks Gain expertise in tackling time series problems, from forecasting future trends to classifying patterns and anomaly detection Purchase of the print or Kindle book includes a free PDF eBook Book Description Most organizations exhibit a time-dependent structure in their processes, including fields such as finance. By leveraging time series analysis and forecasting, these organizations can make informed decisions and optimize their performance. Accurate forecasts help reduce uncertainty and enable better planning of operations. Unlike traditional approaches to forecasting, deep learning can process large amounts of data and help derive complex patterns. Despite its increasing relevance, getting the most out of deep learning requires significant technical expertise. This book guides you through applying deep learning to time series data with the help of easy-to-follow code recipes. You'll cover time series problems, such as forecasting, anomaly detection, and classification. This deep learning book will also show you how to solve these problems using different deep neural network architectures, including convolutional neural networks (CNNs) or transformers. As you progress, you'll use PyTorch, a popular deep learning framework based on Python to build production-ready prediction solutions. By the end of this book, you'll have learned how to solve different time series tasks with deep learning using the PyTorch ecosystem. What you will learn Grasp the core of time series analysis and unleash its power using Python Understand PyTorch and how to use it to build deep learning models Discover how to transform a time series for training transformers Understand how to deal with various time series characteristics Tackle forecasting problems, involving univariate or multivariate data Master time series classification with residual and convolutional neural networks Get up to speed with solving time series anomaly detection problems using autoencoders and generative adversarial networks (GANs) Who this book is for If you're a machine learning enthusiast or someone who wants to learn more about building forecasting applications using deep learning, this book is for you. Basic knowledge of Python programming and machine learning is required to get the most out of this book.
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  • 14
    Online Resource
    Online Resource
    [Sebastopol, California] : O'Reilly Media, Inc.
    ISBN: 9781098171353 , 1098171357
    Language: English
    Pages: 1 online resource (5 pages)
    Edition: [First edition].
    Series Statement: Shortcuts
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Python (Langage de programmation)
    Abstract: Build your knowledge of Python with this Shortcuts collection. Focusing on common problems involving text manipulation, many of these tasks can be solved using built-in methods of strings. More complicated operations may require regular expressions or the creation of a full-fledged parser.
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  • 15
    ISBN: 9781837639533
    Language: English
    Pages: 1 online resource (814 pages) , illustrations
    Edition: Second edition.
    Series Statement: Expert insight
    DDC: 001.4/226028566
    Keywords: Information visualization Computer programs ; Visual analytics Data processing ; Data mining Computer programs ; Business intelligence Computer programs ; R (Computer program language) ; Python (Computer program language) ; Visualisation de l'information ; Logiciels ; Analyse visuelle ; Informatique ; Exploration de données (Informatique) ; Logiciels ; R (Langage de programmation) ; Python (Langage de programmation)
    Abstract: The latest edition of this book delves deep into advanced analytics, focusing on enhancing Python and R proficiency within Power BI. New chapters cover optimizing Python and R settings, utilizing Intel's Math Kernel Library (MKL) for performance boosts, and addressing integration challenges. Techniques for managing large datasets beyond available RAM, employing the Parquet data format, and advanced fuzzy matching algorithms are explored. Additionally, it discusses leveraging SQL Server Language Extensions to overcome traditional Python and R limitations in Power BI. It also helps in crafting sophisticated visualizations using the Grammar of Graphics in both R and Python. This Power BI book will help you master data validation with regular expressions, import data from diverse sources, and apply advanced algorithms for transformation. You'll learn how to safeguard personal data in Power BI with techniques like pseudonymization, anonymization, and data masking. You'll also get to grips with the key statistical features of datasets by plotting multiple visual graphs in the process of building a machine learning model. The book will guide you on utilizing external APIs for enrichment, enhancing I/O performance, and leveraging Python and R for analysis. You'll reinforce your learning with questions at the end of each chapter.
    Note: Includes bibliographical references and index
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  • 16
    Online Resource
    Online Resource
    [Place of publication not identified] : Packt Publishing
    ISBN: 9781836204473 , 1836204477
    Language: English
    Pages: 1 online resource (1 video file (4 hr., 34 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Computer programming ; Python (Langage de programmation) ; Programmation (Informatique) ; computer programming ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: An immersive video course designed to introduce and deepen your understanding of Object-Oriented Programming (OOP) principles within the Python ecosystem. Through a hands-on approach, instructors Vonne and Justin guide you from the foundational setup and OOP basics--encapsulation, abstraction, inheritance, and polymorphism--to the creation of a dynamic text-based game, MonsterSlash. This course is structured to enhance your programming skills by applying OOP techniques to reduce code redundancy, promote reusability, and streamline your coding workflow. You'll embark on a project-driven learning path that not only solidifies theoretical concepts but also puts them into practice by developing a fully functional game. As the course progresses, you'll refine your game, add complexity, and implement advanced OOP strategies, culminating in version 2 of MonsterSlash that features enhanced gameplay elements. Whether you're a beginner eager to explore programming or an intermediate looking to sharpen your OOP skills in Python, this course offers valuable insights and skills for your development arsenal. What you will learn Set up your Python environment for OOP development. Understand and apply the four pillars of OOP in Python. Create, extend, and refine classes and objects. Develop a text-based game from scratch using OOP principles. Employ inheritance and composition to optimize your code. Refactor and enhance your game with advanced OOP techniques. Audience This course is ideal for individuals interested in Python programming, especially those curious about object-oriented programming. Beginners will find the course accessible, while intermediate programmers can deepen their OOP knowledge. Prior exposure to basic Python syntax is helpful but not required. About the Authors ACI Learning: ACI Learning trains leaders in Cybersecurity, Audit, and Information Technology. Whether starting an IT career, mastering a profession, or developing a team, they provide essential support at every step. Justin Dennison: Justin leads AWS and developer content creation for ITProTV. He has experience in multiple programming languages. His certifications include AWS Certified Solutions Architect -- Associate, AWS Certified Developer -- Associate, AWS Certified Cloud Practitioner, Oracle Certified Associate, Java SE 7 Programmer. Vonne Smith: Vonne leads the content development for the OfficeProTV and CreativeProTV channels. She has over a decade of experience teaching Office and Adobe applications both online and in the classroom. Certifications: Microsoft Office Master 2016.
    Note: Online resource; title from title details screen (O'Reilly, viewed April 23, 2024)
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  • 17
    Online Resource
    Online Resource
    Hoboken, New Jersey : John Wiley & Sons, Inc.
    ISBN: 9781394236152
    Language: English
    Pages: 1 online resource (704 pages) , illustrations
    Edition: 3rd edition.
    Series Statement: For dummies
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Computer programming ; Python (Langage de programmation) ; Programmation (Informatique) ; computer programming
    Abstract: Python All-in-One For Dummies is your one-stop source for answers to all your Python questions. From creating apps to building complex web sites to sorting big data, Python provides a way to get the work done. This book is great as a starting point for those new to coding, and it also makes a perfect reference for experienced coders looking for more than the basics. Apply your Python skills to data analysis, learn to write AI-assisted code using GitHub CoPilot, and discover many more exciting uses for this top programming language.
    Note: Includes index
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  • 18
    Online Resource
    Online Resource
    [Sebastopol, California] : O'Reilly Media, Inc.
    ISBN: 9781098171360 , 1098171365
    Language: English
    Pages: 1 online resource (5 pages)
    Edition: [First edition].
    Series Statement: Shortcuts
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Python (Langage de programmation)
    Abstract: Build your knowledge of Python with this Shortcuts collection. Focusing on common problems involving text manipulation, many of these tasks can be solved using built-in methods of strings. More complicated operations may require regular expressions or the creation of a full-fledged parser.
    Library Location Call Number Volume/Issue/Year Availability
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  • 19
    Online Resource
    Online Resource
    Tōkyō-to Shinjuku-ku : Orairī Japan
    Orig.schr. Ausgabe: 初版.
    Title: Raspberry Piクックブック : : 第 4版 /
    Publisher: 東京都新宿区 : オライリー・ジャパン
    ISBN: 9784814400508 , 4814400500
    Language: Japanese
    Pages: 1 online resource (560 pages) , illustrations.
    Edition: Shohan.
    Series Statement: Make: projects
    Uniform Title: Raspberry Pi cookbook
    DDC: 004.1675
    Keywords: Raspberry Pi (Computer) ; Python (Computer program language) ; Application software Development ; Raspberry Pi (Ordinateur) ; Python (Langage de programmation) ; Logiciels d'application ; Développement
    Abstract: "If you've started to work with Raspberry Pi, you know that Raspberry Pi's capabilities are continually expanding. The fourth edition of this popular cookbook provides more than 200 hands-on recipes (complete with code) that show you how to run this tiny low-cost computer with Linux, program it with Python, hook it up to sensors and motors, and use it with the Internet of things (IoT). This new edition includes new chapters on the Raspberry Pi Pico and machine learning with the Raspberry Pi."--
    Note: In Japanese.
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  • 20
    Online Resource
    Online Resource
    [Place of publication not identified] : Manning Publications
    Language: English
    Pages: 1 online resource (1 video file (9 hr., 46 min.)) , sound, color.
    Edition: Video edition.
    DDC: 006.3/1
    Keywords: Machine learning ; Data mining ; SQL (Computer program language) ; Scripting languages (Computer science) ; Apprentissage automatique ; Exploration de données (Informatique) ; SQL (Langage de programmation) ; Langages de script (Informatique) ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: Practical methods for analyzing your data with graphs, revealing hidden connections and new insights. Graphs are the natural way to represent and understand connected data. This book explores the most important algorithms and techniques for graphs in data science, with concrete advice on implementation and deployment. You don't need any graph experience to start benefiting from this insightful guide. These powerful graph algorithms are explained in clear, jargon-free text and illustrations that makes them easy to apply to your own projects. In Graph Algorithms for Data Science you will learn: Labeled-property graph modeling Constructing a graph from structured data such as CSV or SQL NLP techniques to construct a graph from unstructured data Cypher query language syntax to manipulate data and extract insights Social network analysis algorithms like PageRank and community detection How to translate graph structure to a ML model input with node embedding models Using graph features in node classification and link prediction workflows Graph Algorithms for Data Science is a hands-on guide to working with graph-based data in applications like machine learning, fraud detection, and business data analysis. It's filled with fascinating and fun projects, demonstrating the ins-and-outs of graphs. You'll gain practical skills by analyzing Twitter, building graphs with NLP techniques, and much more. About the Technology A graph, put simply, is a network of connected data. Graphs are an efficient way to identify and explore the significant relationships naturally occurring within a dataset. This book presents the most important algorithms for graph data science with examples from machine learning, business applications, natural language processing, and more. About the Book Graph Algorithms for Data Science shows you how to construct and analyze graphs from structured and unstructured data. In it, you'll learn to apply graph algorithms like PageRank, community detection/clustering, and knowledge graph models by putting each new algorithm to work in a hands-on data project. This cutting-edge book also demonstrates how you can create graphs that optimize input for AI models using node embedding. What's Inside Creating knowledge graphs Node classification and link prediction workflows NLP techniques for graph construction About the Reader For data scientists who know machine learning basics. Examples use the Cypher query language, which is explained in the book. About the Author Toma¿ℓ Bratani♯⁻ works at the intersection of graphs and machine learning. Arturo Geigel was the technical editor for this book. Quotes Undoubtedly the quickest route to grasping the practical applications of graph algorithms. Enjoyable and informative, with real-world business context and practical problem-solving. - Roger Yu, Feedzai Brilliantly eases you into graph-based applications. - Sumit Pal, Independent Consultant I highly recommend this book to anyone involved in analyzing large network databases. - Ivan Herreros, talentsconnect Insightful and comprehensive. The author's expertise is evident. Be prepared for a rewarding journey. - Michal ¿ tefa¿⁸©Łk, Volke.
    Note: Online resource; title from title details screen (O'Reilly, viewed April 15, 2024)
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  • 21
    Online Resource
    Online Resource
    [Place of publication not identified] : O'Reilly Media, Inc.
    Language: English
    Pages: 1 online resource (1 video file (3 hr., 57 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Machine learning ; Computer programming ; Python (Langage de programmation) ; Apprentissage automatique ; Programmation (Informatique) ; computer programming ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: In this course, you will learn to use Python for data science and gain the essential skills to analyze and visualize data effectively. Whether you are a data analyst, data scientist, business analyst, or data engineer, this course will provide you with the knowledge and tools to excel in your role. Python is a versatile language that offers powerful libraries for data manipulation, visualization, and machine learning, making it the go-to choice for data professionals. The course solves the problem of understanding and leveraging Python's capabilities for data science by providing business use cases. You will learn to use popular Python libraries such as Pandas, Matplotlib, Seaborn, and Scikit-learn to analyze and visualize data, perform statistical analysis, and build predictive models. By the end of the course, you will have a solid foundation in Python for data science and be ready to apply your skills to real-world projects. What you'll learn and how you can apply it Upon completion of this course, learners will be able to: Apply Python programming concepts for data analysis and visualization Manipulate and analyze data using Pandas Create informative and visually appealing data visualizations using Matplotlib and Seaborn Perform statistical analysis to gain insights from the data Build and evaluate machine learning models for predictive analytics This course is for you because... You're a Python beginner who wants to learn how to manage data with Python. You're a traditional data analyst who has experience with tools like Excel and Tableau, but wants to learn how to manage data with Python. You're a finance, healthcare, ecommerce, or manufacturing/logistics professional looking to become adept in Python and data science. Prerequisites No prior knowledge of Python or Data analytics is needed. All course files can be accessed in this GitHub repository.
    Note: Online resource; title from title details screen (O'Reilly, viewed April 23, 2024)
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  • 22
    Online Resource
    Online Resource
    [Place of publication not identified] : Packt Publishing
    ISBN: 9781836204459 , 1836204450
    Language: English
    Pages: 1 online resource (1 video file (3 hr., 8 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.1/17
    Keywords: Python (Computer program language) ; Application software Development ; Python (Langage de programmation) ; Logiciels d'application ; Développement ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: """Abstracting with Functions"" is a meticulously curated video course designed for technical professionals eager to master the art of function creation in Python. Through a comprehensive series of videos, learners are taken on a journey that begins with the basics of what functions are and why they are pivotal in programming. The course underscores the significance of functions in collecting logic into reusable chunks, thereby fostering more readable and maintainable codebases. Starting with an introductory overview, the course swiftly moves to dissect the anatomy of functions, from the simplest forms without arguments to more complex functions featuring multiple positional and keyword arguments. Each episode, hosted by dynamic duos such as Aubri and Ronnie or Justin and Zach, not only discusses the syntax and theoretical aspects but also delves into practical demonstrations and the subtleties of function creation, such as edge cases and argument types. The importance of understanding functions is also linked to professional development, highlighting their relevance in networking and certification exams. By the end of the course, learners will have a solid grasp of how to efficiently abstract logic through functions, enabling the construction of more sophisticated and scalable programs. What you will learn Understand the fundamental concept of functions. Explore the syntax and creation of functions in Python. Distinguish between various types of functions. Learn advanced topics such as keyword arguments. Use mixed arguments to enhance function versatility. Grasp the significance of functions in different contexts. Audience Individuals at the beginning of their coding journey who want to learn best practices early on, and those with some experience in Python or other programming languages looking to deepen their understanding of functions and how to use them more effectively in their projects will find this course quite useful. About the Authors ACI Learning: ACI Learning trains leaders in Cybersecurity, Audit, and Information Technology. Whether starting an IT career, mastering a profession, or developing a team, they provide essential support at every step. Justin Dennison: Justin leads AWS and developer content creation for ITProTV. He has experience in multiple programming languages. His certifications include AWS Certified Solutions Architect -- Associate, AWS Certified Developer -- Associate, AWS Certified Cloud Practitioner, Oracle Certified Associate, Java SE 7 Programmer. Zachary Memos: Zachary Memos is a show host with 30+ years of on-camera experience. He brings his wit and charm to the camera while helping bring out the best in the ITProTV subject matter experts.".
    Note: Online resource; title from title details screen (O'Reilly, viewed April 23, 2024)
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  • 23
    Online Resource
    Online Resource
    [Place of publication not identified] : Packt Publishing
    ISBN: 9781836206071 , 1836206070
    Language: English
    Pages: 1 online resource (1 video file (2 hr., 27 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: ChatGPT ; Python (Computer program language) ; Computer programming ; Artificial intelligence ; Python (Langage de programmation) ; Programmation (Informatique) ; Intelligence artificielle ; computer programming ; artificial intelligence ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: "Unlock the world of conversational AI with ""Create Your Own ChatGPT Clone using Python,"" a comprehensive video course designed to teach you the intricacies of AI model interactions. Starting with a solid introduction and setup requirements, this course swiftly moves into hands-on exercises where you'll engage with the ChatGPT API using Python. You'll not only learn about API parameters and endpoints but also how to weave these components into a responsive Python FastAPI service. Transitioning from Python to front-end development, the course empowers you to create a React project, giving life to your ChatGPT clone with engaging styles and functionalities. The journey continues into the nuances of fine-tuning models, where you'll tailor ChatGPT solutions to fit specific needs, offering personalized experiences. The course culminates in strategic model selection, ensuring you're equipped to choose the most effective GPT model for your project's requirements, capped off with a cohesive summary tying all learned concepts together. What you will learn Navigate the setup for ChatGPT API interaction. Create a Python FastAPI for ChatGPT. Construct and style a ChatGPT clone in a React environment. Customize ChatGPT models through fine-tuning techniques. Select the optimal GPT model for specific project needs. Synthesize course knowledge in a comprehensive project. Audience Geared towards Python developers keen on building AI chatbots, and AI and NLP enthusiasts looking to delve into chatbot development, this course suits students and professionals eager for hands-on AI and Python experience. A foundational grasp of Python, React, and basic API interactions is assumed, catering to innovators who want to unlock the potential of conversational AI. About the Author Eduonix Learning Solutions: Eduonix Learning Solutions is at the forefront of technology training, boasting a vast global reach with over 1 million students across 200+ courses. With a rich history spanning over a decade, Eduonix's mission is to deliver industry-standard, high-quality training content created by a team of seasoned industry professionals. Their comprehensive curriculum covers a wide range of technologies, from Web and Mobility to Enterprise, Database, and Server Administration. Eduonix is dedicated to teaching technology in the context of real-world professional applications, ensuring that learners are equipped with the skills needed to excel in today's tech-driven landscape.".
    Note: Online resource; title from title details screen (O'Reilly, viewed April 22, 2024)
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  • 24
    ISBN: 9781837632114 , 1837632111 , 9781837636457
    Language: English
    Pages: 1 online resource
    Edition: 1st edition.
    Parallel Title: Erscheint auch als
    DDC: 006.3/12
    Keywords: Data mining ; Systems engineering ; Exploration de données (Informatique) ; Ingénierie des systèmes ; systems engineering
    Abstract: Gain a holistic understanding of the analytics engineering lifecycle by integrating principles from both data analysis and engineering Key Features Discover how analytics engineering aligns with your organization's data strategy Access insights shared by a team of seven industry experts Tackle common analytics engineering problems faced by modern businesses Purchase of the print or Kindle book includes a free PDF eBook Book Description Navigate the world of data analytics with Fundamentals of Analytics Engineering--guiding you from foundational concepts to advanced techniques of data ingestion and warehousing, data lakehouse, and data modeling. Written by a team of 7 industry experts, this book helps you to transform raw data into structured insights. In this book, you'll discover how to clean, filter, aggregate, and reformat data, and seamlessly serve it across diverse platforms. With practical guidance, you'll also learn how to build a simple data platform using Airbyte for ingestion, DuckDB for warehousing, dbt for transformations, and Tableau for visualization. From data quality and observability to fostering collaboration on codebases, you'll discover effective strategies for ensuring data integrity and driving collaborative success. As you advance, you'll become well-versed with the CI/CD principles for automated code building, testing, and deployment--laying the foundation for consistent and reliable pipelines. And with invaluable insights into gathering business requirements, documenting complex business logic, and the importance of data governance, you'll develop a holistic understanding of the analytics lifecycle. By the end of this book, you'll be armed with the essential techniques and best practices for developing scalable analytics solutions from end to end. What you will learn Design and implement data pipelines from ingestion to serving data Explore best practices for data modeling and schema design Gain insights into the use of cloud-based analytics platforms and tools for scalable data processing Understand the principles of data governance and collaborative coding Comprehend data quality management in analytics engineering Gain practical skills in using analytics engineering tools to conquer real-world data challenges Who this book is for This book is for data engineers and data analysts considering pivoting their careers into analytics engineering. Analytics engineers who want to upskill and search for gaps in their knowledge will also find this book helpful, as will other data professionals who want to understand the value of analytics engineering in their organization's journey toward data maturity. To get the most out of this book, you should have a basic understanding of data analysis and engineering concepts such as data cleaning, visualization, ETL and data warehousing.
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  • 25
    ISBN: 9781394220625 , 1394220626 , 1394220634 , 9781394220649 , 1394220642 , 9781394220632 , 9781394220618
    Language: English
    Pages: 1 online resource (512 pages) , illustrations (some color)
    Parallel Title: Erscheint auch als
    DDC: 006.3/1
    Keywords: Machine learning ; Quantum computing ; Python (Computer program language) ; Apprentissage automatique ; Informatique quantique ; Python (Langage de programmation) ; Machine learning ; Python (Computer program language) ; Quantum computing
    Abstract: "Machine learning (ML) and quantum computing are two technologies that have the potential to allow us to solve complex, previously impossible problems and help speed up areas such as model training or pattern recognition. The future of computing will certainly be comprised of classical, biologically inspired, and quantum computing. The intersection between quantum computing and AI/ML has received considerable attention in recent years and has enabled the development of quantum machine learning algorithms such as quantum-enhanced Support Vector Machines (QSVMs), QSVM multiclass classification, variational quantum classifiers or quantum generative adversarial networks (qGANs)."--
    Note: Includes bibliographical references and index. - Description based on online resource; title from digital title page (viewed on March 26, 2024)
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  • 26
    Online Resource
    Online Resource
    [Place of publication not identified] : Manning Publications
    Language: English
    Pages: 1 online resource (1 sound file (9 hr., 35 min.))
    Edition: [First edition].
    DDC: 006.3/1
    Keywords: Machine learning ; Data mining ; SQL (Computer program language) ; Scripting languages (Computer science) ; Apprentissage automatique ; Exploration de données (Informatique) ; SQL (Langage de programmation) ; Langages de script (Informatique) ; Audiobooks ; Livres audio
    Abstract: Practical methods for analyzing your data with graphs, revealing hidden connections and new insights. Graphs are the natural way to represent and understand connected data. This book explores the most important algorithms and techniques for graphs in data science, with concrete advice on implementation and deployment. You don't need any graph experience to start benefiting from this insightful guide. These powerful graph algorithms are explained in clear, jargon-free text and illustrations that makes them easy to apply to your own projects. In Graph Algorithms for Data Science you will learn: Labeled-property graph modeling Constructing a graph from structured data such as CSV or SQL NLP techniques to construct a graph from unstructured data Cypher query language syntax to manipulate data and extract insights Social network analysis algorithms like PageRank and community detection How to translate graph structure to a ML model input with node embedding models Using graph features in node classification and link prediction workflows Graph Algorithms for Data Science is a hands-on guide to working with graph-based data in applications like machine learning, fraud detection, and business data analysis. It's filled with fascinating and fun projects, demonstrating the ins-and-outs of graphs. You'll gain practical skills by analyzing Twitter, building graphs with NLP techniques, and much more. About the Technology A graph, put simply, is a network of connected data. Graphs are an efficient way to identify and explore the significant relationships naturally occurring within a dataset. This book presents the most important algorithms for graph data science with examples from machine learning, business applications, natural language processing, and more. About the Book Graph Algorithms for Data Science shows you how to construct and analyze graphs from structured and unstructured data. In it, you'll learn to apply graph algorithms like PageRank, community detection/clustering, and knowledge graph models by putting each new algorithm to work in a hands-on data project. This cutting-edge book also demonstrates how you can create graphs that optimize input for AI models using node embedding. What's Inside Creating knowledge graphs Node classification and link prediction workflows NLP techniques for graph construction About the Reader For data scientists who know machine learning basics. Examples use the Cypher query language, which is explained in the book. About the Author Toma¿ℓ Bratani♯⁻ works at the intersection of graphs and machine learning. Arturo Geigel was the technical editor for this book. Quotes Undoubtedly the quickest route to grasping the practical applications of graph algorithms. Enjoyable and informative, with real-world business context and practical problem-solving. - Roger Yu, Feedzai Brilliantly eases you into graph-based applications. - Sumit Pal, Independent Consultant I highly recommend this book to anyone involved in analyzing large network databases. - Ivan Herreros, talentsconnect Insightful and comprehensive. The author's expertise is evident. Be prepared for a rewarding journey. - Michal ¿ tefa¿⁸©Łk, Volke.
    Note: Online resource; title from title details screen (O'Reilly, viewed April 1, 2024)
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  • 27
    Online Resource
    Online Resource
    San Francisco : No Starch Press
    Language: English
    Pages: 1 online resource (352 pages) , illustrations
    Edition: Second edition.
    Parallel Title: Erscheint auch als
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Electronic apparatus and appliances Automatic control ; Arduino (Programmable controller) Programming ; Raspberry Pi (Computer) Programming
    Abstract: Harness the power of Python as you turn code into tangible creations with Python Playground, a collection of 15 inventive projects that will expand your programming horizons, spark your curiosity, and elevate your coding skills. Go beyond the basics as you write programs to generate art and music, simulate real-world phenomena, and interact with hardware, all through the use of Python and common libraries such as numpy, matplotlib, and Pillow. New to this edition: We’ve expanded your playground with five new projects: you’ll draw fractals, bring Conway’s Game of Life into 3D space, and use a Raspberry Pi and Python to create a musical instrument, an IoT garden monitor, and even a machine learning–driven speech recognition system. Whether you’re a seasoned professional or just getting started, you’ll find Python Playground to be a great way to learn, experiment with, and master this versatile programming language. Covers Python 3.x
    Note: Includes index. - Description based on print version record
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  • 28
    Online Resource
    Online Resource
    [Place of publication not identified] : Pearson
    ISBN: 9780138298432 , 0138298432
    Language: English
    Pages: 1 online resource (1 video file (2 hr., 22 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Computer programming ; Python (Langage de programmation) ; Programmation (Informatique) ; computer programming ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: Sneak Peek The Sneak Peek program provides early access to Pearson video products and is exclusively available to Safari subscribers. Content for titles in this program is made available throughout the development cycle, so products may not be complete, edited, or finalized, including video post-production editing.
    Note: Online resource; title from title details screen (O'Reilly, viewed January 23, 2024)
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  • 29
    Online Resource
    Online Resource
    [Place of publication not identified] : Pearson
    ISBN: 9780138297947 , 0138297940
    Language: English
    Pages: 1 online resource (1 video file (2 hr., 29 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Computer programming ; Web site development ; Web applications ; Python (Langage de programmation) ; Programmation (Informatique) ; Sites Web ; Développement ; Applications Web ; computer programming ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: Sneak Peek The Sneak Peek program provides early access to Pearson video products and is exclusively available to Safari subscribers. Content for titles in this program is made available throughout the development cycle, so products may not be complete, edited, or finalized, including video post-production editing. 2.5 Hours of Video Instruction Explore Python's capabilities for Data Science and Machine Learning, the topics of greatest import these days in the tech world. Python has risen to popularity as one of the most versatile and beginner-friendly programming languages. Its simplicity, readability, and extensive libraries make it a powerful language for a wide variety of different domains. It's widely used in web development, data analysis, scientific computing, artificial intelligence, and automation. Python's versatility and large community support make it an excellent language to kickstart your programming journey. This course offers a hands-on approach to building your Python skills through a series of practical projects from scratch. Hone your expertise in areas such as data analysis, machine learning, web scraping, and more. Related Learning: Watch and learn from Shaun's other videos: Functional Programming Projects with Python 3 About the Instructor: Shaun is a Senior Software Developer who specializes in Full-stack development and Software Architecture. He manages teams of developers, as well as teaches many hundreds of thousands more how to create enterprise-ready applications. Shaun's online courses have over 300,000 learners largely because of his passion for development and his focus on helping people apply their programming skills in the real world. He is a life-long programmer and problem-solving addict whose goal is to help people solve meaningful problems by mastering the art of software development. Please don't hesitate to get in touch with him about any opportunities or if you'd like to stay up to date on his other courses and live trainings. Skill Level: Intermediate-Advanced What You Will Learn: Each project will include some different aspect of data science/ machine learning with Python that it will be both accessible and engaging while you advance your skill set. Perform Sentiment Analysis on real-world text Work with Image Recognition Tools Scrape Basic Data from Websites And much more! Who Should Take This Course: Job titles: Software developer, Data analyst/scientist, Machine Learning Engineer, Web Developer, DevOps Engineer. Course Requirements: Prerequisites: Python experience and app development background About Pearson Video Training: Pearson publishes expert-led video tutorials covering a wide selection of technology topics designed to teach you the skills you need to succeed. These professional and personal technology videos feature world-leading author instructors published by your trusted technology brands: Addison-Wesley, Cisco Press, Pearson IT Certification, Prentice Hall, Sams, and Que. Topics include IT Certification, Network Security, Cisco Technology, Programming, Web Development, Mobile Development, and more. Learn more about Pearson Video training at http://www.informit.com/video.
    Note: Online resource; title from title details screen (O'Reilly, viewed January 23, 2024)
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  • 30
    ISBN: 9781098148362 , 1098148363
    Language: English
    Pages: 1 online resource
    Parallel Title: Erscheint auch als
    DDC: 332.64/20285
    Keywords: Electronic trading of securities ; Python (Computer program language) ; Valeurs mobilières ; Commerce électronique ; Python (Langage de programmation)
    Abstract: Deep learning is rapidly gaining momentum in the world of finance and trading. But for many professional traders, this sophisticated field has a reputation for being complex and difficult. This hands-on guide teaches you how to develop a deep learning trading model from scratch using Python, and it also helps you create and backtest trading algorithms based on machine learning and reinforcement learning. Sofien Kaabar--financial author, trading consultant, and institutional market strategist--introduces deep learning strategies that combine technical and quantitative analyses. By fusing deep learning concepts with technical analysis, this unique book presents outside-the-box ideas in the world of financial trading. This A-Z guide also includes a full introduction to technical analysis, evaluating machine learning algorithms, and algorithm optimization. Understand and create machine learning and deep learning models Explore the details behind reinforcement learning and see how it's used in time series Understand how to interpret performance evaluation metrics Examine technical analysis and learn how it works in financial markets Create technical indicators in Python and combine them with ML models for optimization Evaluate the models' profitability and predictability to understand their limitations and potential.
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  • 31
    Language: English
    Pages: 1 online resource (300 pages) , illustrations
    Edition: First edition.
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Computer programming ; Python (Langage de programmation) ; Programmation (Informatique) ; computer programming
    Abstract: Keeping up with the Python ecosystem can be daunting. Its developer tooling doesn't provide the out-of-the-box experience native to languages like Rust and Go. When it comes to long-term project maintenance or collaborating with others, every Python project faces the same problem: how to build reliable workflows beyond local development while staying in sync with the evolving ecosystem. With this hands-on guide, Python developers will learn how to forge the moving parts of a Python project into an easy-to-use toolchain, using state-of-the-art tools including Poetry, Nox, GitHub Actions, Dependabot, pytest, mypy, pre-commit, Black, Ruff, and more. Author Claudio Jolowicz shows you how to create robust Python project structures complete with unit tests, static analysis, code formatting, type checking, and documentation as well as continuous integration and delivery.
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  • 32
    ISBN: 9781484299913 , 1484299914
    Language: English
    Pages: 1 online resource (xxii, 403 pages) , illustrations
    Edition: 2nd ed.
    Parallel Title: Erscheint auch als
    Keywords: Quantum computing ; Python (Computer program language) ; Informatique quantique ; Python (Langage de programmation)
    Abstract: Learn to write algorithms and program in the new field of quantum computing. This second edition is updated to equip you with the latest knowledge and tools needed to be a complex problem-solver in this ever-evolving landscape. The book has expanded its coverage of current and future advancements and investments by IT companies in this emerging technology. Most chapters are thoroughly revised to incorporate the latest updates to IBM Quantum's systems and offerings, such as improved algorithms, integrating hardware advancements, software enhancements, bug fixes, and more. You'll examine quantum computing in the cloud and run experiments there on a real quantum device. Along the way you'll cover game theory with the Magic Square, an example of quantum pseudo-telepathy. You'll also learn to write code using QISKit, Python SDK, and other APIs such as QASM and execute it against simulators (local or remote) or a real quantum computer. Then peek inside the inner workings of the Bell states for entanglement, Grover's algorithm for linear search, Shor's algorithm for integer factorization, and other algorithms in the fields of optimization, and more. Finally, you'll learn the current quantum algorithms for entanglement, random number generation, linear search, integer factorization, and others. By the end of this book, you'll understand how quantum computing provides massive parallelism and significant computational speedups over classical computers What You'll Learn Write algorithms that provide superior performance over their classical counterparts Create a quantum number generator: the quintessential coin flip with a quantum twist Examine the quantum algorithms in use today for random number generation, linear search, and more Discover quantum teleportation Handle the counterfeit coin problem, a classic puzzle Put your knowledge to the test with more than 150 practice exercises Who This Book Is For Developers, programmers, computer science researchers, teachers, and students.
    Note: Description based upon print version of record
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  • 33
    Online Resource
    Online Resource
    San Francisco : No Starch Press
    ISBN: 9781718503250 , 1718503253
    Language: English
    Pages: 1 online resource
    Parallel Title: Erscheint auch als
    DDC: 519.2/3
    Keywords: Algorithms ; Numbers, Random ; Python (Computer program language) ; Algorithmes ; Nombres aléatoires ; Python (Langage de programmation) ; algorithms ; Algorithms ; Numbers, Random ; Python (Computer program language)
    Abstract: "The Art of Randomness teaches readers to harness the power of randomness (and Python code) to solve real-world problems in programming, science, and art through hands-on experiments-from simulating evolution to encrypting messages to making machine-learning algorithms. Each chapter describes how randomness plays into the given topic area, then proceeds to demonstrate its problem-solving role with hands-on experiments to work through using Python code"--
    Note: Includes bibliographical references and index. - Description based on print version record and CIP data provided by publisher; resource not viewed
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  • 34
    Online Resource
    Online Resource
    [Place of publication not identified] : Packt Publishing
    ISBN: 9781835464694 , 1835464696
    Language: English
    Pages: 1 online resource (1 video file (8 hr., 44 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.3
    Keywords: Application program interfaces (Computer software) ; Software architecture ; Python (Computer program language) ; Interfaces de programmation d'applications ; Architecture logicielle ; Python (Langage de programmation) ; APIs (interfaces) ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: This course offers a detailed exploration of FastAPI, a cutting-edge Python framework for API development. The course starts with basic API and REST principles, quickly advancing to practical application for a thorough understanding of both theory and practice. The curriculum progresses logically, starting with the basics of FastAPI, including app setup, API routing, linting, and formatting. Participants will create a social media API, manage post and comments, and learn code organization with APIRouter, followed by practical testing experience using pytest. A significant portion of the course focuses on asynchronous databases, vital for scalable application development. It covers database setup, connection, and integration within FastAPI. The course also delves into Python logging techniques, crucial for debugging and monitoring FastAPI applications. It also covers user authentication, an essential element in modern web apps. It includes practical training on JWTs, password hashing, authentication management, and database user relationships, alongside addressing many-to-many database relationships and user email confirmation strategies. In later stages, the course addresses advanced topics like file uploads, background image generation tasks, and deployment methodologies, including continuous integration with GitHub Actions. What you will learn Build and structure a FastAPI application Implement and test RESTful APIs with FastAPI Manage asynchronous database operations Configure and utilize Python logging in FastAPI Secure applications with user authentication and JWTs Handle complex database relationships Deploy FastAPI applications and manage them effectively Audience This course is ideal for aspiring back-end developers, testers looking to integrate automation into their workflows, and front-end developers seeking a deeper understanding of server-side processes. This course will particularly benefit those with a basic grasp of programming and a desire to specialize in the fast-paced realm of web development, API construction, and database management using FastAPI. Prior programming experience in any language is recommended; beginners should consider a basic Python course first, as all required software is provided for free. About the Author Jose Salvatierra Fuentes: Jose, a passionate educator in the realm of coding and software development, has dedicated over 7 years to teaching online. He founded Teclado with a vision to democratize software development education, striving to ensure comprehensive understanding for his students. His approach makes learning coding a clear, rewarding journey, connecting the dots that once seemed obscure. Specializing in Python and JavaScript, Jose excels in web and backend development. He's proficient in various libraries and frameworks, including Flask, React, React Native, and AngularJS. His expertise extends to working with UNIX systems, MongoDB, PostgreSQL, and crafting advanced system architectures. Jose's commitment is to make the learning process both efficient and enjoyable, guiding students to mastery in software development.
    Note: Online resource; title from title details screen (O'Reilly, viewed January 23, 2024)
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  • 35
    ISBN: 9798868800085
    Language: English
    Pages: 1 online resource (538 pages) , illustrations
    Edition: Second edition.
    Parallel Title: Erscheint auch als
    Keywords: Anomaly detection (Computer security) ; Python (Computer program language) ; Machine learning ; Détection d'anomalies (Sécurité informatique) ; Python (Langage de programmation) ; Apprentissage automatique
    Abstract: This beginner-oriented book will help you understand and perform anomaly detection by learning cutting-edge machine learning and deep learning techniques. This updated second edition focuses on supervised, semi-supervised, and unsupervised approaches to anomaly detection. Over the course of the book, you will learn how to use Keras and PyTorch in practical applications. It also introduces new chapters on GANs and transformers to reflect the latest trends in deep learning. Beginning Anomaly Detection Using Python-Based Deep Learning begins with an introduction to anomaly detection, its importance, and its applications. It then covers core data science and machine learning modeling concepts before delving into traditional machine learning algorithms such as OC-SVM and Isolation Forest for anomaly detection using scikit-learn. Following this, the authors explain the essentials of machine learning and deep learning, and how to implement multilayer perceptrons for supervised anomaly detection in both Keras and PyTorch. From here, the focus shifts to the applications of deep learning models for anomaly detection, including various types of autoencoders, recurrent neural networks (via LSTM), temporal convolutional networks, and transformers, with the latter three architectures applied to time-series anomaly detection. This edition has a new chapter on GANs (Generative Adversarial Networks), as well as new material covering transformer architecture in the context of time-series anomaly detection. After completing this book, you will have a thorough understanding of anomaly detection as well as an assortment of methods to approach it in various contexts, including time-series data. Additionally, you will have gained an introduction to scikit-learn, GANs, transformers, Keras, and PyTorch, empowering you to create your own machine learning- or deep learning-based anomaly detectors. What You Will Learn Understand what anomaly detection is, why it it is important, and how it is applied Grasp the core concepts of machine learning. Master traditional machine learning approaches to anomaly detection using scikit-kearn. Understand deep learning in Python using Keras and PyTorch Process data through pandas and evaluate your model's performance using metrics like F1-score, precision, and recall Apply deep learning to supervised, semi-supervised, and unsupervised anomaly detection tasks for tabular datasets and time series applications Who This Book Is For Data scientists and machine learning engineers of all levels of experience interested in learning the basics of deep learning applications in anomaly detection.
    Note: Includes index
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  • 36
    Language: English
    Pages: 1 online resource (352 pages) , illustrations
    Edition: Fifth edition.
    Series Statement: Zed Shaw's Hard way series
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Computer programming ; Python (Langage de programmation) ; Programmation (Informatique) ; computer programming
    Abstract: Zed Shaw has created the world's most reliable system for learning Python. Follow it and you will succeed--just like the millions of beginners Zed has taught to date! You bring the discipline, persistence, and attention; the author supplies the masterful knowledge you need to succeed. In Learn Python the Hard Way, Fifth Edition, you'll learn Python by working through 60 lovingly crafted exercises. Read them. Type in the code. Run it. Fix your mistakes. Repeat. As you do, you'll learn how a computer works, how to solve problems, and how to enjoy programming...even when it's driving you crazy.
    Note: Includes bibliographical references and index
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  • 37
    ISBN: 9781484297452 , 1484297458
    Language: English
    Pages: 1 online resource (xxi, 233 pages) , illustrations
    Edition: [First edition].
    Parallel Title: Erscheint auch als
    Keywords: Machine learning Computer simulation ; Debugging in computer science Computer programs ; Python (Computer program language) ; Apprentissage automatique ; Simulation par ordinateur ; Débogueurs ; Python (Langage de programmation)
    Abstract: This book is for those who wish to understand how Python debugging is and can be used to develop robust and reliable AI, machine learning, and cloud computing software. It will teach you a novel pattern-oriented approach to diagnose and debug abnormal software structure and behavior. The book begins with an introduction to the pattern-oriented software diagnostics and debugging process that, before performing Python debugging, diagnoses problems in various software artifacts such as memory dumps, traces, and logs. Next, you’ll learn to use various debugging patterns through Python case studies that model abnormal software behavior. You’ll also be exposed to Python debugging techniques specific to cloud native and machine learning environments and explore how recent advances in AI/ML can help in Python debugging. Over the course of the book, case studies will show you how to resolve issues around environmental problems, crashes, hangs, resource spikes, leaks, and performance degradation. This includes tracing, logging, and analyziing memory dumps using native WinDbg and GDB debuggers. Upon completing this book, you will have the knowledge and tools needed to employ Python debugging in the development of AI, machine learning, and cloud computing applications.
    Note: Includes bibliographical references and index
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  • 38
    Online Resource
    Online Resource
    [Place of publication not identified] : Scatterplot Press
    ISBN: 9781835461969
    Language: English
    Pages: 1 online resource (146 pages) , illustrations
    Edition: First edition.
    DDC: 005.13/3
    Keywords: Machine learning ; Python (Computer program language) ; Data mining ; Apprentissage automatique ; Python (Langage de programmation) ; Exploration de données (Informatique)
    Abstract: The course starts by setting the foundation with an introduction to machine learning, Python, and essential libraries, ensuring you grasp the basics before diving deeper. It then progresses through exploratory data analysis, data scrubbing, and pre-model algorithms, equipping you with the skills to understand and prepare your data for modeling. The journey continues with detailed walkthroughs on creating, evaluating, and optimizing machine learning models, covering key algorithms such as linear and logistic regression, support vector machines, k-nearest neighbors, and tree-based methods. Each section is designed to build upon the previous, reinforcing learning and application of concepts. Wrapping up, the course introduces the next steps, including an introduction to Python for newcomers, ensuring a comprehensive understanding of machine learning applications.
    Note: Includes bibliographical references
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  • 39
    ISBN: 9781484298619 , 1484298616
    Language: English
    Pages: 1 online resource (578 p.)
    Edition: 2nd ed.
    Parallel Title: Erscheint auch als
    Keywords: Python (Computer program language) ; Microcontrollers ; Computer programming ; Python (Langage de programmation) ; Microcontrôleurs ; Programmation (Informatique) ; computer programming
    Abstract: This book will help you quickly learn to program for microcontrollers and IoT devices without a lot of study and expense. MicroPython and controllers that support it eliminate the need for programming in a C-like language, making the creation of IoT applications and devices easier and more accessible than ever. MicroPython for the Internet of Things is ideal for readers new to electronics and the world of IoT. Specific examples are provided covering a range of supported devices, sensors, and MicroPython boards such as the Raspberry Pi Pico and the Arduino Nano Connect RP2040 board. Programming for microcontrollers has never been easier. The book takes a practical and hands-on approach without a lot of detours into the depths of theory. It'll show you a faster and easier way to program microcontrollers and IoT devices, teach you MicroPython, a variant of one of the most widely used scripting languages, and is written to be accessible to those new to electronics. After completing this book, and its fun example projects, you'll be ready to ready to use MicroPython to develop your own IoT applications. What You Will Learn Program in MicroPython Understand sensors and basic electronics Develop your own IoT projects Build applications for popular boards such as Raspberry Pi Pico and Arduino Nano Connect RP2040 Load MicroPython on compatible boards Interface with hardware breakout boards Connect hardware to software through MicroPython Explore connecting your microcontroller to the cloud Develop IoT projects for the cloud Who This Book Is For Anyone interested in building IoT solutions without the heavy burden of programming in C++ or C. The book also appeals to those wanting an easier way to work with hardware than is provided by platforms that require more complex programming environments.
    Note: Description based upon print version of record. - Conditional Statements
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  • 40
    Online Resource
    Online Resource
    Shelter Island, NY : Manning Publications
    ISBN: 9781633438453 , 1633438457 , 9781638354369 , 1638354367
    Language: English
    Pages: 1 online resource (248 pages) , illustrations
    Edition: [First edition].
    Parallel Title: Erscheint auch als
    DDC: 629.8/92
    Keywords: Robotics ; Python (Computer program language) ; Raspberry Pi (Computer) ; Robotique ; Python (Langage de programmation) ; Raspberry Pi (Ordinateur)
    Abstract: Build Your Own Robot is a project-based guide that takes you from spinning your first DC motor to programming a mobile robot that you can control from your phone or computer. You’ll write simple Python code to help your new friend spin, move, and find its way. You’ll even teach it to track faces and fetch snacks. Plus, a helpful hardware purchasing guide makes it easy to find exactly what you need to get started!
    Note: Includes index
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  • 41
    Online Resource
    Online Resource
    [Place of publication not identified] : Packt Publishing
    ISBN: 9781835885628 , 1835885624
    Language: English
    Pages: 1 online resource (1 video file (11 hr., 11 min.)) , sound, color.
    Edition: [First edition].
    DDC: 006.3
    Keywords: Artificial intelligence ; Python (Computer program language) ; Intelligence artificielle ; Python (Langage de programmation) ; artificial intelligence ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: Embark on a transformative learning experience with 'Master ChatGPT and OpenAI APIs By Building AI Tools in Python.' This immersive course takes you from the basics of ChatGPT and OpenAI's potent APIs through a journey of building dynamic AI-powered tools. Discover the magic behind ChatGPT's conversational prowess and dive deep into the neural networks and transformers that make it tick. You'll start by creating and managing your ChatGPT account, understanding the model's anatomy, and grasping the limitations and capabilities of AI language models. Transitioning from theory to hands-on practice, the course guides you through content creation, code generation, and the intricacies of prompt engineering. Moreover, you'll venture into the realms of generative AI with Midjourney, craft AI-driven applications, and harness the synergy of OpenAI and DALL-E for on-the-fly image generation. This course demystifies the AI concepts crucial in today's technology landscape, providing you with the skills to innovate and excel in the burgeoning field of AI. What you will learn Navigate the foundational elements of ChatGPT and OpenAI APIs Generate creative content and code with ChatGPT's language model Design and implement AI applications with user-friendly interfaces Master the art of prompt engineering for optimized AI interactions Build AI-powered tools and images using OpenAI and DALL-E Develop secure, intelligent applications with advanced Python techniques Audience This course welcomes everyone from entrepreneurs to artists and developers, aiming to learn about cutting-edge AI technologies and build AI-powered applications. Basic programming knowledge is preferred but not mandatory, making this course accessible to a wide range of learners. About the Author Paulo Dichone: Paulo Dichone, a seasoned software engineer and AWS Cloud Practitioner, is renowned for his expertise in Android, Flutter, and AWS, as well as being a best-selling instructor. Paulo has successfully imparted his knowledge to over 200,000 students across 175 countries, specializing in mobile app development for Android and iOS, web development, and AWS Cloud. His teaching philosophy centers on empowering students to excel as developers and AWS cloud practitioners, regardless of their prior experience. Beyond his professional pursuits, Paulo is devoted to his family, enjoys playing the guitar and mandolin, and loves to travel. He is committed to guiding students to achieve their highest potential in the tech industry.
    Note: Online resource; title from title details screen (O'Reilly, viewed March 4, 2024)
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  • 42
    ISBN: 9798868802218
    Language: English
    Pages: 1 online resource (220 p.)
    Parallel Title: Erscheint auch als
    Keywords: Application software Development ; Information visualization ; Python (Computer program language) ; Dashboards (Management information systems) ; Logiciels d'application ; Développement ; Visualisation de l'information ; Python (Langage de programmation) ; Tableaux de bord (Gestion)
    Abstract: Create interactive and data-driven dashboards using Python. This hands-on guide is a practical resource for those (with modest programming skills) in scientific and engineering fields looking to leverage Python's power for data visualization and analysis in a user-friendly dashboard format. You'll begin by gaining a fundamental understanding of Python programming, including data types, lists, dictionaries, and data structures. The book then delves into the world of reactive programming with Plotly and Dash, offering a hands-on approach to building interactive web-based dashboards. Next, you'll see how to work with online data, how to scrape and clean datasets, and keep files up-to-date. The book also guides you through planning a dashboard prototype, outlining project tasks, trends, forecasts, spectra, and other design considerations. It concludes with a discussion of how the dashboard can be used for data visualization of real data, explaining the usefulness of tools such as spectra. By providing detailed examples for download and customization, Prototyping Python Dashboards for Scientists and Engineers will equip you with the skills needed to jumpstart your own development efforts. What You'll Learn Design a dashboard with Python Convert and filter Excel formatted files to produce CSV files Create browser-served graphics with PLOTLY Generate polynomial trend lines for forecasting Build a Unix service to share your dashboard Who This Book Is For Scientists, engineers, students, programmers, and data enthusiasts who aspire to harness Python's potential for data visualization and analysis through the creation of interactive dashboards. Many will be pragmatic programmers with modest skills and limited resources who mainly want to see a working solution they could emulate.
    Note: Description based upon print version of record
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  • 43
    ISBN: 9798868801587
    Language: English
    Pages: 1 online resource (xvii, 256 pages) , illustrations.
    Parallel Title: Erscheint auch als
    DDC: 006.3
    Keywords: Computational intelligence ; Artificial intelligence ; Data mining ; Big data ; Intelligence informatique ; Intelligence artificielle ; Exploration de données (Informatique) ; artificial intelligence
    Abstract: Understand and apply the design patterns outlined in this book to design, develop, and deploy scalable AI solutions that meet your organization's needs and drive innovation in the era of intelligent automation. This book begins with an overview of scalable AI systems and the importance of design patterns in creating robust intelligent solutions. It covers fundamental concepts and techniques for achieving scalability in AI systems, including data engineering practices and strategies. The book also addresses scalable algorithms, models, infrastructure, and architecture considerations. Additionally, it discusses deployment, productionization, real-time and streaming data, edge computing, governance, and ethics in scalable AI. Real-world case studies and best practices are presented, along with insights into future trends and emerging technologies. The book focuses on scalable AI and design patterns, providing an understanding of the challenges involved in developing AI systems that can handle large amounts of data, complex algorithms, and real-time processing. By exploring scalability, you will be empowered to design and implement AI solutions that can adapt to changing data requirements. What You Will Learn Develop scalable AI systems that can handle large volumes of data, complex algorithms, and real-time processing Know the significance of design patterns in creating robust intelligent solutions Understand scalable algorithms and models to handle extensive data and computing requirements and build scalable AI systems Be aware of the ethical implications of scalable AI systems Who This Book Is For AI practitioners, data scientists, and software engineers with intermediate-level AI knowledge and experience.
    Note: Description based upon print version of record
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  • 44
    Online Resource
    Online Resource
    [Place of publication not identified] : Packt Publishing
    ISBN: 9781835885925 , 1835885926
    Language: English
    Pages: 1 online resource (1 video file (8 hr., 44 min.)) , sound, color.
    Edition: [First edition].
    DDC: 004.6
    Keywords: Artificial intelligence ; Computer programming ; Chatbots ; Application program interfaces (Computer software) ; Python (Computer program language) ; Intelligence artificielle ; Programmation (Informatique) ; Interfaces de programmation d'applications ; Python (Langage de programmation) ; artificial intelligence ; computer programming ; APIs (interfaces) ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: This comprehensive masterclass takes you on a transformative journey into the realm of LangChain and Large Language Models, equipping you with the skills to build autonomous AI tools. Starting with the basics, you'll set up your development environment, including OpenAI API and Python, and progress to advanced topics like LangChain's architecture, prompt templates, and parsers. The course meticulously guides you through creating complex chains, memory models, and agents, culminating in the development of practical applications such as PDF extractors, newsletter generators, and multi-document chatbots. With hands-on tutorials, you'll learn to leverage LangChain for tasks ranging from document loading and splitting to embedding vector stores for semantic similarity searches. By the end, you'll have the knowledge to implement AI in creative and impactful ways, from image-to-text conversion to building interactive chatbots and more, all while navigating the ethical considerations of AI deployment. What you will learn Configure OpenAI API and Python for AI development Create and manipulate LangChain prompt templates and parsers Implement LangChain memory models and chains for complex AI applications Develop real-world applications, including newsletter generators and chatbots Work with LangChain embeddings and vector stores for semantic searches Navigate the ethical and copyright implications of AI-generated content Audience This course is designed for a broad audience interested in artificial intelligence, from data scientists enhancing projects with AI and LangChain, to product managers boosting user experience with AI features. AI enthusiasts, tech innovators, and programmers will deepen their understanding of LangChain, unlocking new opportunities in AI-driven development and pioneering next-gen solutions. While specific knowledge of Python is not necessary, familiarity with programming concepts is essential. About the Author Paulo Dichone: Paulo Dichone, a seasoned software engineer and AWS Cloud Practitioner, is renowned for his expertise in Android, Flutter, and AWS, as well as being a best-selling instructor. Paulo has successfully imparted his knowledge to over 200,000 students across 175 countries, specializing in mobile app development for Android and iOS, web development, and AWS Cloud. His teaching philosophy centers on empowering students to excel as developers and AWS cloud practitioners, regardless of their prior experience. Beyond his professional pursuits, Paulo is devoted to his family, enjoys playing the guitar and mandolin, and loves to travel. He is committed to guiding students to achieve their highest potential in the tech industry.
    Note: Online resource; title from title details screen (O'Reilly, viewed March 4, 2024)
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  • 45
    Online Resource
    Online Resource
    [Place of publication not identified] : Manning Publications
    Language: English
    Pages: 1 online resource (1 sound file (5 hr., 7 min.))
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) Juvenile literature ; Computer programming Juvenile literature ; Python (Computer program language) ; Computer programming ; Python (Langage de programmation) ; Ouvrages pour la jeunesse ; Programmation (Informatique) ; Ouvrages pour la jeunesse ; Audiobooks ; Livres audio
    Abstract: Time to take an adventure with friends! Team up with Erik and Simon to learn Python the easy way. This colorful book uses engaging questions and lively conversations to introduce computer programming to young readers one step at a time. In A Pythonic Adventure, you will learn useful Python skills like: Installing Python Working with files Creating text-based dialogs and menus Using if/then, loops, lists, dictionaries, and input/output Building web applications Making your web apps look super professional It's fun to learn with friends! In A Pythonic Adventure you'll meet Erik and Simon, two brothers who are just beginning their Python journey. Join them as they chat about the language, learn the basics, and build some cool programs. The book's dialogue helps young programmers understand complex concepts much more easily. It's the perfect way for young programmers (and their parents) to get started. There's no boring lessons or dull exercises in this adventure. You'll follow Erik and Simon's questions and mistakes, discover how to write programs with a team, and get a chance to create applications you can use in your daily life. By the time they're done reading, young learners will not only know how to write code, they'll know how to think about problems like professional developers. All code in this book runs on Mac, Windows, Linux, and Raspberry Pi. About the Technology Computer programming is an adventure, full of new experiences, challenges, triumphs, and mistakes. In A Pythonic Adventure, you'll join brothers Erik and Simon as they learn to create their first Python program. Written especially for young readers, this book is the perfect introduction to a skill that will last a lifetime! About the Book A Pythonic Adventure teaches you to code by asking questions, making errors, and trying out different solutions--just like in real life. As you go, you'll create a web application for a coffee shop step-by-step, from your first online menu to saving orders in a database. And this unique tutorial goes deeper than other beginner books. You'll learn and practice important skills like planning applications, finding bugs, and managing user expectations. What's Inside Installing Python Creating text-based dialogs and menus Building web applications Making your web apps look professional About the Reader For readers aged 10+. Perfect for adult beginners, too! About the Author Pavel Anni is a Principal Customer Engineer at SambaNova Systems, and has also worked for Sun Microsystems, Oracle, and Red Hat. Quotes Pavel's conversational writing style is engaging and entertaining. If Plato wrote a programming book, he'd have written it like this one! - Nicholas Tollervey, Anaconda A great way to build your first application. Th e final web app is impressive! - Andrew R. Freed, IBM This book was perfect for sparking my son into coding with Python--now I can't stop him! - Ben McNamara, DataGeek This book awakened my daughters' interest in programming. They will be part of the future. - Walter Alexander Mata L©đpez, University of Colima.
    Note: Online resource; title from title details screen (O'Reilly, viewed March 4, 2024)
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  • 46
    ISBN: 9781835081495 , 1835081495 , 9781835081167
    Language: English
    Pages: 1 online resource (220 p.)
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Computer software Development ; Python (Langage de programmation)
    Abstract: Unleash DevOps excellence with Python and its ecosystem of tools for seamless orchestration on both local and cloud platforms, such as GCP, AWS, and AzureKey FeaturesIntegrate Python into DevOps for streamlined workflows, task automation, and improved collaborationCombine the principles of Python and DevOps into a unified approach for problem solving.
    Note: Description based upon print version of record. - Sample 1: Running fleet maintenance on multiple instance fleets at once
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  • 47
    Online Resource
    Online Resource
    Shelter Island : Manning Publication Co.
    ISBN: 9781617299469 , 1617299464
    Language: English
    Pages: 1 online resource (xx, 330 pages) , illustrations.
    Parallel Title: Erscheint auch als
    DDC: 006.3/1
    Keywords: Machine learning ; Data mining ; SQL (Computer program language) ; Scripting languages (Computer science) ; Apprentissage automatique ; Exploration de données (Informatique) ; SQL (Langage de programmation) ; Langages de script (Informatique) ; Data mining ; Machine learning ; Scripting languages (Computer science) ; SQL (Computer program language)
    Abstract: "Labeled-property graph modeling Constructing a graph from structured data such as CSV or SQL NLP techniques to construct a graph from unstructured data Cypher query language syntax to manipulate data and extract insights Social network analysis algorithms like PageRank and community detection How to translate graph structure to a ML model input with node embedding models Using graph features in node classification and link prediction workflows Graph Algorithms for Data Science is a hands-on guide to working with graph-based data in applications like machine learning, fraud detection, and business data analysis. It's filled with fascinating and fun projects, demonstrating the ins-and-outs of graphs. You'll gain practical skills by analyzing Twitter, building graphs with NLP techniques, and much more. You don't need any graph experience to start benefiting from this insightful guide. These powerful graph algorithms are explained in clear, jargon-free text and illustrations that makes them easy to apply to your own projects. about the technology Graphs reveal the relationships in your data. Tracking these interlinking connections reveals new insights and influences and lets you analyze each data point as part of a larger whole. This interconnected data is perfect for machine learning, as well as analyzing social networks, communities, and even product recommendations. about the book Graph Algorithms for Data Science teaches you how to construct graphs from both structured and unstructured data. You'll learn how the flexible Cypher query language can be used to easily manipulate graph structures, and extract amazing insights. The book explores common and useful graph algorithms like PageRank and community detection/clustering algorithms. Each new algorithm you learn is instantly put into action to complete a hands-on data project, including modeling a social network! Finally, you'll learn how to utilize graphs to upgrade your machine learning, including utilizing node embedding models and graph neural networks."--
    Note: Includes index. - Description based on print version record
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  • 48
    ISBN: 9781804612415 , 1804612413 , 9781804618127
    Language: English
    Pages: 1 online resource
    Edition: 1st edition.
    Parallel Title: Erscheint auch als
    DDC: 005.13/3
    Keywords: Machine learning ; Python (Computer program language) ; Data mining ; Apprentissage automatique ; Python (Langage de programmation) ; Exploration de données (Informatique)
    Abstract: Join the data-centric revolution and master the concepts, techniques, and algorithms shaping the future of AI and ML development, using Python Key Features Grasp the principles of data centricity and apply them to real-world scenarios Gain experience with quality data collection, labeling, and synthetic data creation using Python Develop essential skills for building reliable, responsible, and ethical machine learning solutions Purchase of the print or Kindle book includes a free PDF eBook Book Description In the rapidly advancing data-driven world where data quality is pivotal to the success of machine learning and artificial intelligence projects, this critically timed guide provides a rare, end-to-end overview of data-centric machine learning (DCML), along with hands-on applications of technical and non-technical approaches to generating deeper and more accurate datasets. This book will help you understand what data-centric ML/AI is and how it can help you to realize the potential of 'small data'. Delving into the building blocks of data-centric ML/AI, you'll explore the human aspects of data labeling, tackle ambiguity in labeling, and understand the role of synthetic data. From strategies to improve data collection to techniques for refining and augmenting datasets, you'll learn everything you need to elevate your data-centric practices. Through applied examples and insights for overcoming challenges, you'll get a roadmap for implementing data-centric ML/AI in diverse applications in Python. By the end of this book, you'll have developed a profound understanding of data-centric ML/AI and the proficiency to seamlessly integrate common data-centric approaches in the model development lifecycle to unlock the full potential of your machine learning projects by prioritizing data quality and reliability. What you will learn Understand the impact of input data quality compared to model selection and tuning Recognize the crucial role of subject-matter experts in effective model development Implement data cleaning, labeling, and augmentation best practices Explore common synthetic data generation techniques and their applications Apply synthetic data generation techniques using common Python packages Detect and mitigate bias in a dataset using best-practice techniques Understand the importance of reliability, responsibility, and ethical considerations in ML/AI Who this book is for This book is for data science professionals and machine learning enthusiasts looking to understand the concept of data-centricity, its benefits over a model-centric approach, and the practical application of a best-practice data-centric approach in their work. This book is also for other data professionals and senior leaders who want to explore the tools and techniques to improve data quality and create opportunities for small data ML/AI in their organizations.
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  • 49
    ISBN: 9781805125419 , 1805125419 , 9781805127161
    Language: English
    Pages: 1 online resource.
    Edition: Third Edition.
    Series Statement: Expert insight
    Parallel Title: Erscheint auch als
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Natural language processing (Computer science) ; Bayesian statistical decision theory ; Python (Langage de programmation) ; Traitement automatique des langues naturelles ; Théorie de la décision bayésienne
    Abstract: Learn the fundamentals of Bayesian modeling using state-of-the-art Python libraries, such as PyMC, ArviZ, Bambi, and more, guided by an experienced Bayesian modeler who contributes to these libraries Key Features Conduct Bayesian data analysis with step-by-step guidance Gain insight into a modern, practical, and computational approach to Bayesian statistical modeling Enhance your learning with best practices through sample problems and practice exercises Purchase of the print or Kindle book includes a free PDF eBook. Book DescriptionThe third edition of Bayesian Analysis with Python serves as an introduction to the main concepts of applied Bayesian modeling using PyMC, a state-of-the-art probabilistic programming library, and other libraries that support and facilitate modeling like ArviZ, for exploratory analysis of Bayesian models; Bambi, for flexible and easy hierarchical linear modeling; PreliZ, for prior elicitation; PyMC-BART, for flexible non-parametric regression; and Kulprit, for variable selection. In this updated edition, a brief and conceptual introduction to probability theory enhances your learning journey by introducing new topics like Bayesian additive regression trees (BART), featuring updated examples. Refined explanations, informed by feedback and experience from previous editions, underscore the book's emphasis on Bayesian statistics. You will explore various models, including hierarchical models, generalized linear models for regression and classification, mixture models, Gaussian processes, and BART, using synthetic and real datasets. By the end of this book, you will possess a functional understanding of probabilistic modeling, enabling you to design and implement Bayesian models for your data science challenges. You'll be well-prepared to delve into more advanced material or specialized statistical modeling if the need arises. What you will learn Build probabilistic models using PyMC and Bambi Analyze and interpret probabilistic models with ArviZ Acquire the skills to sanity-check models and modify them if necessary Build better models with prior and posterior predictive checks Learn the advantages and caveats of hierarchical models Compare models and choose between alternative ones Interpret results and apply your knowledge to real-world problems Explore common models from a unified probabilistic perspective Apply the Bayesian framework's flexibility for probabilistic thinking Who this book is for If you are a student, data scientist, researcher, or developer looking to get started with Bayesian data analysis and probabilistic programming, this book is for you. The book is introductory, so no previous statistical knowledge is required, although some experience in using Python and scientific libraries like NumPy is expected.
    Note: Includes bibliographical references and index. - Online resource; title from PDF title page (EBSCO, viewed February 29, 2024)
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  • 50
    Online Resource
    Online Resource
    [Sebastopol, California] : O'Reilly Media, Inc.
    ISBN: 9781098146443 , 1098146441
    Language: English
    Pages: 1 online resource
    Edition: First edition.
    Parallel Title: Erscheint auch als
    DDC: 004
    Keywords: Electronic data processing ; Big data ; Database management ; Data mining ; Données volumineuses ; Bases de données ; Gestion ; Exploration de données (Informatique)
    Abstract: "This practical guide provides a collection of techniques and best practices that are generally overlooked in most data engineering and data science pedagogy. A common misconception is that great data scientists are experts in the ""big themes"" of the discipline--machine learning and programming. But most of the time, these tools can only take us so far. In practice, the smaller tools and skills really separate a great data scientist from a not-so-great one. Taken as a whole, the lessons in this book make the difference between an average data scientist candidate and a qualified data scientist working in the field. Author Daniel Vaughan has collected, extended, and used these skills to create value and train data scientists from different companies and industries. With this book, you will: Understand how data science creates value Deliver compelling narratives to sell your data science project Build a business case using unit economics principles Create new features for a ML model using storytelling Learn how to decompose KPIs Perform growth decompositions to find root causes for changes in a metric Daniel Vaughan is head of data at Clip, the leading paytech company in Mexico. He's the author of Analytical Skills for AI and Data Science (O'Reilly)."
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  • 51
    Online Resource
    Online Resource
    Sebastopol, CA : O'Reilly Media, Inc.
    Language: English
    Pages: 1 online resource (350 pages) , illustrations
    Edition: First edition.
    DDC: 658.4/033
    Keywords: Decision making Statistical methods ; Business intelligence ; Management Statistical methods ; Data mining ; Machine learning ; Prise de décision ; Méthodes statistiques ; Gestion ; Méthodes statistiques ; Exploration de données (Informatique) ; Apprentissage automatique
    Abstract: The surging predictive analytics market is expected to grow from USD10.5 billion today to USD28 billion by 2026. With the rise in automation across industries, the increase in data-driven decision-making, and the proliferation of IoT devices, predictive analytics has become an operational necessity in today's forward-thinking companies. If you're a data professional, you need to be aligned with your company's business activities more than ever before. This practical book provides the background, tools, and best practices necessary to help you design, implement, and operationalize predictive analytics in the cloud. Author Nooruddin Abbas Ali, principal solutions architect at MongoDB, brings you up to speed through industry use cases and end-to-end hands-on examples.
    Note: Includes bibliographical references
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  • 52
    ISBN: 9781837636303
    Language: English
    Pages: 1 online resource (326 pages) , illustrations
    Edition: Third edition.
    DDC: 005.75/65
    Keywords: Data mining ; Quantitative research
    Abstract: Transform your data into insights with must-know techniques and mathematical concepts to unravel the secrets hidden within your data Key Features Learn practical data science combined with data theory to gain maximum insights from data Discover methods for deploying actionable machine learning pipelines while mitigating biases in data and models Explore actionable case studies to put your new skills to use immediately Purchase of the print or Kindle book includes a free PDF eBook Book Description Principles of Data Science bridges mathematics, programming, and business analysis, empowering you to confidently pose and address complex data questions and construct effective machine learning pipelines. This book will equip you with the tools to transform abstract concepts and raw statistics into actionable insights. Starting with cleaning and preparation, you'll explore effective data mining strategies and techniques before moving on to building a holistic picture of how every piece of the data science puzzle fits together. Throughout the book, you'll discover statistical models with which you can control and navigate even the densest or the sparsest of datasets and learn how to create powerful visualizations that communicate the stories hidden in your data. With a focus on application, this edition covers advanced transfer learning and pre-trained models for NLP and vision tasks. You'll get to grips with advanced techniques for mitigating algorithmic bias in data as well as models and addressing model and data drift. Finally, you'll explore medium-level data governance, including data provenance, privacy, and deletion request handling. By the end of this data science book, you'll have learned the fundamentals of computational mathematics and statistics, all while navigating the intricacies of modern ML and large pre-trained models like GPT and BERT. What you will learn Master the fundamentals steps of data science through practical examples Bridge the gap between math and programming using advanced statistics and ML Harness probability, calculus, and models for effective data control Explore transformative modern ML with large language models Evaluate ML success with impactful metrics and MLOps Create compelling visuals that convey actionable insights Quantify and mitigate biases in data and ML models Who this book is for If you are an aspiring novice data scientist eager to expand your knowledge, this book is for you. Whether you have basic math skills and want to apply them in the field of data science, or you excel in programming but lack the necessary mathematical foundations, you'll find this book useful. Familiarity with Python programming will further enhance your learning experience.
    Note: Includes index
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  • 53
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'REILLY MEDIA
    ISBN: 9781098148454 , 1098148452
    Language: English
    Pages: 1 online resource
    Parallel Title: Erscheint auch als
    DDC: 005.75/65
    Keywords: Entity-relationship modeling ; Data mining ; Modèles entité-association ; Exploration de données (Informatique)
    Abstract: Entity resolution is a key analytic technique that enables you to identify multiple data records that refer to the same real-world entity. With this hands-on guide, product managers, data analysts, and data scientists will learn how to add value to data by cleansing, analyzing, and resolving datasets using open source Python libraries and cloud APIs. Author Michael Shearer shows you how to scale up your data matching processes and improve the accuracy of your reconciliations. You'll be able to remove duplicate entries within a single source and join disparate data sources together when common keys aren't available. Using real-world data examples, this book helps you gain practical understanding to accelerate the delivery of real business value. With entity resolution, you'll build rich and comprehensive data assets that reveal relationships for marketing and risk management purposes, key to harnessing the full potential of ML and AI.
    Note: Includes bibliographical references and index
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  • 54
    Language: English
    Pages: 1 online resource (400 pages) , illustrations
    Edition: First edition.
    DDC: 005.7
    Keywords: Big data ; Data mining ; Python (Computer program language) ; Données volumineuses ; Exploration de données (Informatique) ; Python (Langage de programmation)
    Abstract: Want to speed up your data analysis and work with larger-than-memory datasets? Python Polars offers a blazingly fast, multithreaded, and elegant API for data loading, manipulation, and processing. With this hands-on guide, you'll walk through every aspect of Polars and learn how to tackle practical use cases using real-world datasets. Jeroen Janssens and Thijs Nieuwdorp from Xomnia in Amsterdam show you how this superfast DataFrame library is perfect for efficient data wrangling, ETL pipelines, and so much more. This book helps you quickly learn the syntax and understand Polars' underlying concepts. You don't need to have experience with pandas or Spark, but if you do, this book will help you make a smooth transition.
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  • 55
    Online Resource
    Online Resource
    Sebastopol : O'Reilly Media, Incorporated
    ISBN: 9781098145316 , 1098145313
    Language: English
    Pages: 1 online resource (352 p.)
    Edition: 3rd ed.
    Parallel Title: Erscheint auch als
    DDC: 006.3/12
    Keywords: Data mining ; Python (Computer program language)
    Abstract: If programming is magic, then web scraping is surely a form of wizardry. By writing a simple automated program, you can query web servers, request data, and parse it to extract the information you need. This thoroughly updated third edition not only introduces you to web scraping but also serves as a comprehensive guide to scraping almost every type of data from the modern web. Part I focuses on web scraping mechanics: using Python to request information from a web server, performing basic handling of the server's response, and interacting with sites in an automated fashion. Part II explores a variety of more specific tools and applications to fit any web scraping scenario you're likely to encounter. Parse complicated HTML pages Develop crawlers with the Scrapy framework Learn methods to store the data you scrape Read and extract data from documents Clean and normalize badly formatted data Read and write natural languages Crawl through forms and logins Scrape JavaScript and crawl through APIs Use and write image-to-text software Avoid scraping traps and bot blockers Use scrapers to test your website.
    Note: Description based upon print version of record. - Markov Models
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  • 56
    Online Resource
    Online Resource
    [Place of publication not identified] : Packt Publishing
    ISBN: 9781835463444 , 1835463444
    Language: English
    Pages: 1 online resource (1 video file (10 hr., 14 min.)) , sound, color.
    Edition: [First edition].
    DDC: 006.7/6
    Keywords: Web site development Computer programs ; Application software Development ; Python (Computer program language) ; Sites Web ; Systèmes-auteur ; Logiciels d'application ; Développement ; Python (Langage de programmation) ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: Next.js is a popular open-source JavaScript framework designed to make web development with React efficient and scalable. Next.js adds layers of abstraction to React and simplifies the process of building modern web applications. It provides a set of conventions and features that enhance the development experience, making it easier to create performant and SEO-friendly applications. This comprehensive Next.js course unfolds by beginning with an introduction to web development fundamentals, as it progresses through React basics, advanced Next.js concepts, and real-world deployment strategies. We will explore key topics such as server-side rendering (SSR), client-side rendering (CSR), static site generation (SSG), and incremental static regeneration (ISR). The course offers hands-on experience with a final project, covering everything from structuring applications to optimizing for performance and SEO. The modular format accommodates varying skill levels, ensuring a well-rounded and practical learning experience for all learners. Upon completion of this Next.js course, you will become proficient in web development fundamentals, React essentials, and advanced Next.js concepts. Through hands-on experience, master server-side rendering, client-side rendering, dynamic routing, and performance and scalability in real-world scenarios. What you will learn Master SSR, CSR, and SSG for optimized web development Explore React basics and advanced component development in Next.js Implement Next.js best practices for efficient and scalable web applications Learn to create dynamic routes for versatile content handling Deploy fully functional applications using Vercel and Git/GitHub workflows Enhance applications for search engines and social platforms through metadata and SEO practices Audience This Next.js course is tailored for a diverse audience, catering to both entry-level and seasoned developers. Ideal for junior developers, it provides a strong foundation in web development fundamentals, React basics, and advanced Next.js concepts. Intermediate developers can enhance their skills and gain mastery in the latest features of Next.js. Senior web developers seeking to stay updated with modern concepts will find valuable insights for optimizing web applications. No programming experience is required, but basic web development and JavaScript understanding is desirable for the course. About the Author Clarian North: Clarian North is a recognized industry-certified instructor, CEO of Orbital LLC, and a senior project engineer with over 90K enrolments worldwide. His students have gone on to work for some of the biggest production companies such as Universal, Google, Amazon, Warner, and the BBC. He has contributed to viral streams, grown a unique digital imprint in over 80 countries, and been featured in Rolling Stone, Billboard, Guardian, Bloomberg, and Vice. He has worked for majors, indies, and international publishing houses, including Grammy-nominated and award-winning productions, mixing for Emirates Airline Inflight Radio, and producing for Kompakt Records. He is dedicated to giving accessible and comprehensive tech courses, teaching complex subject matter with clear and example-based explanations, and guiding students through complex techniques with just a computer and free software.
    Note: Online resource; title from title details screen (O'Reilly, viewed January 31, 2024)
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  • 57
    ISBN: 9781633437784 , 1633437787
    Language: English
    Pages: 1 online resource (296 pages) , illustrations
    Edition: [First edition].
    Parallel Title: Erscheint auch als Porter, Leo Learn AI-assisted Python programming
    DDC: 005.13/3
    Keywords: ChatGPT ; Python (Computer program language) ; Computer programming ; Natural language processing (Computer science) ; Artificial intelligence Computer programs ; Python (Langage de programmation) ; Programmation (Informatique) ; Traitement automatique des langues naturelles ; Intelligence artificielle ; Logiciels ; computer programming ; Einführung ; Künstliche Intelligenz ; Programmierung ; Python
    Abstract: Writing computer programs in Python just got a lot easier! Use AI-assisted coding tools like GitHub Copilot and ChatGPT to turn your ideas into applications faster than ever. AI has changed the way we write computer programs. With tools like Copilot and ChatGPT, you can describe what you want in plain English, and watch your AI assistant generate the code right before your eyes. It’s perfect for beginners, or anyone who’s struggled with the steep learning curve of traditional programming. Learn AI-Assisted Python Programming: With GitHub Copilot and ChatGPT is a hands-on beginner’s guide that is written by two esteemed computer science university professors. It teaches you everything you need to start programming Python in an AI-first world. You’ll hit the ground running, writing prompts that tell your AI-assistant exactly what you want your programs to do. Along the way, you’ll pick up the essentials of Python programming and practice the higher-level thinking you’ll need to create working apps for data analysis, automating tedious tasks, and even video games. The way people write computer programs has changed forever. Using GitHub Copilot, you describe in plain English what you want your program to do, and the AI generates it instantly. This book shows you how to create and improve Python programs using AI—even if you’ve never written a line of computer code before. Spend less time on the slow, low-level programming details and instead learn how an AI assistant can bring your ideas to life immediately. As you go, you’ll even learn enough of the Python language to understand and improve what your AI assistant creates.
    Note: Includes bibliographical references and index
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  • 58
    Online Resource
    Online Resource
    Hoboken, New Jersey : Addison-Wesley Professional
    Language: English
    Pages: 1 online resource (288 pages) , illustrations
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Python (Langage de programmation)
    Abstract: Python is one of the most widely used programming languages in the world. It is used everywhere from primary school education to workaday web development, to the most advanced scientific research institutes of the world. However, like all programming languages, Python has a collection of "Pythonic" ways of accomplishing tasks that are easy to overlook, especially when habits are borrowed wholesale from work in other programming languages. Better Python Code is a guide to Pythonic programming. The book presents common mistakes that Python developers make--even Python developers who have used the language for years--often because Python sometimes presents "attractive nuisances." Throughout, the book is a guide to better programming in the core Python language. Each section shows a concrete but concise example of some misunderstanding or bad habit in action. Each section contains a description of what is wrong with the sample code and a suggestion for one or more better ways to code equivalent functionality without the initial pitfall. Every pitfall addressed in this book reflects foibles, errors, and misunderstandings that the author as seen in concrete, widely used code bases written by experienced developers, over his 25 years of writing Python. Both beginners and developers with decades of experience will learn to correct limitations in the code they write after reflecting on these discussions.
    Note: Includes bibliographical references and index
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  • 59
    Online Resource
    Online Resource
    Berkeley, CA : Apress
    ISBN: 9781484299883 , 1484299884
    Language: English
    Pages: 1 online resource (xxiii, 320 pages) , illustrations
    Edition: Second edition.
    Parallel Title: Erscheint auch als
    Keywords: Python (Computer program language) ; Python (Langage de programmation)
    Abstract: This book, which is designed for middle-school through college-aged students, will arm beginners with solid programming foundations they can carry throughout life. It uses fun and simple language (and programming examples) to teach the fundamentals needed to start the down path of becoming a programmer. Python is a highly flexible language, allowing developers to enter any number of technical fields and is a welcome addition to any resume. With its low learning curve, it makes a great introductory language, as new developers can take the coding fundamentals they learn in Python and apply them to any other language. The second edition builds upon the foundation of the first book, revising all the chapters where the language has changed, updating the commands, code, and examples to bring it up to date with the current version of Python. Since Python is the most popular programming language in the world and can be used in conjunction with other languages - across multiple platforms - it can increase the reader's ability to qualify for a wider range of jobs than other languages. Finally, Python is fun - something not every programming language can boast! You will: Install and configure Python Grasp basic software development principles and syntax Understand the best practices for coding in Python Create applications and debug code.
    Note: Includes index. - Online resource; title from PDF title page (SpringerLink, viewed December 15, 2023)
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  • 60
    ISBN: 9783031353741 , 9783031353734
    Language: Undetermined
    Pages: 1 Online-Ressource (297 p.)
    Keywords: Information technology: general issues ; Geography ; Data mining ; Media studies
    Abstract: This open access book includes methods for retrieval, semantic representation, and analysis of Volunteered Geographic Information (VGI), geovisualization and user interactions related to VGI, and discusses selected topics in active participation, social context, and privacy awareness. It presents the results of the DFG-funded priority program "VGI: Interpretation, Visualization, and Social Computing" (2016-2023). The book includes three parts representing the principal research pillars within the program. Part I "Representation and Analysis of VGI" discusses recent approaches to enhance the representation and analysis of VGI. It includes semantic representation of VGI data in knowledge graphs; machine-learning approaches to VGI mining, completion, and enrichment as well as to the improvement of data quality and fitness for purpose. Part II "Geovisualization and User Interactions related to VGI" book explores geovisualizations and user interactions supporting the analysis and presentation of VGI data. When designing these visualizations and user interactions, the specific properties of VGI data, the knowledge and abilities of different target users, and technical viability of solutions need to be considered. Part III "Active Participation, Social Context and Privacy Awareness" of the book addresses the human impact associated with VGI. It includes chapters on the use of wearable sensors worn by volunteers to record their exposure to environmental stressors on their daily journeys, on the collective behavior of people using location-based social media and movement data from football matches, and on the motivation of volunteers who provide important support in information gathering, filtering and analysis of social media in disaster situations. The book is of interest to researchers and advanced professionals in geoinformation, cartography, visual analytics, data science and machine learning
    Note: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 61
    ISBN: 9789463728485
    Language: Undetermined
    Pages: 1 Online-Ressource (348 p.)
    Series Statement: Digital Studies
    Keywords: Data mining ; Algorithms & data structures ; Media studies ; Algorithmic regimes, datafication, critical data studies, algorithm studies, science and technology studies
    Abstract: Algorithms have risen to become one, if not the central technology for producing, circulating, and evaluating knowledge in multiple societal arenas. In this book, scholars from the social sciences, humanities, and computer science argue that this shift has, and will continue to have, profound implications for how knowledge is produced and what and whose knowledge is valued and deemed valid. To attend to this fundamental change, the authors propose the concept of algorithmic regimes and demonstrate how they transform the epistemological, methodological, and political foundations of knowledge production, sensemaking, and decision-making in contemporary societies. Across sixteen chapters, the volume offers a diverse collection of contributions along three perspectives on algorithmic regimes: the methods necessary to research and design algorithmic regimes, the ways in which algorithmic regimes reconfigure sociotechnical interactions, and the politics engrained in algorithmic regimes
    Note: English
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  • 62
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : IntechOpen
    ISBN: 9781837690275 , 9781837690268 , 9781837690282
    Language: Undetermined
    Pages: 1 Online-Ressource (168 p.)
    Series Statement: Artificial Intelligence 24
    Keywords: Data mining
    Abstract: This book discusses and addresses anomaly detection in the context of artificial intelligence and machine learning advancements. Building on the existing literature, this thorough and timely work is an invaluable resource. It highlights various problems, offers workable solutions to those problems, and allows academic and professional researchers and practitioners to engage in new technologies linked to anomaly detection. This book demystifies the challenges and presents solutions for detecting and understanding network anomalies. Whether you are a seasoned network professional or an enthusiast keen on cyber security, this volume promises insights that will fortify our connected futures. Join us in navigating the complexities of modern networks and championing a safer, more transparent digital era
    Note: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 63
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : JOHN WILEY & SONS
    ISBN: 9781394213085 , 1394213085 , 9781394213146
    Language: English
    Pages: 1 online resource
    Series Statement: For dummies
    Parallel Title: Erscheint auch als
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Programming languages (Electronic computers) ; Data mining
    Abstract: Python for Data Science For Dummies lets you get your hands dirty with data using one of the top programming languages. This beginner's guide takes you step by step through getting started, performing data analysis, understanding datasets and example code, working with Google Colab, sampling data, and beyond. Coding your data analysis tasks will make your life easier, make you more in-demand as an employee, and open the door to valuable knowledge and insights. This new edition is updated for the latest version of Python and includes current, relevant data examples.
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  • 64
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc.
    ISBN: 9781098171377 , 1098171373
    Language: Undetermined
    Pages: 1 online resource
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Web site development ; Python (Langage de programmation) ; Sites Web ; Développement
    Abstract: Build your knowledge of Python with this Shortcuts collection. Focusing on common problems involving text manipulation, many of these tasks can be solved using built-in methods of strings. More complicated operations may require regular expressions or the creation of a full-fledged parser.
    Note: Machine-generated record
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  • 65
    Online Resource
    Online Resource
    Hoboken, NJ : John Wiley & Sons, Inc.
    ISBN: 9781394244119 , 1394244118 , 9781394244102 , 139424410X , 9781394244096
    Language: English
    Pages: 1 online resource
    Series Statement: For dummies
    Parallel Title: Erscheint auch als
    DDC: 005.7
    Keywords: Big data ; Data mining ; Information visualization ; Computer programming ; Exploration de données (Informatique) ; Visualisation de l'information ; Programmation (Informatique) ; computer programming
    Abstract: Data Analytics & Visualization All-in-One For Dummies collects the essential information on mining, organizing, and communicating data, all in one place. Clocking in at around 850 pages, this tome of a reference delivers eight books in one, so you can build a solid foundation of knowledge in data wrangling. Data analytics professionals are highly sought after these days, and this book will put you on the path to becoming one. You’ll learn all about sources of data like data lakes, and you’ll discover how to extract data using tools like Microsoft Power BI, organize the data in Microsoft Excel, and visually present the data in a way that makes sense using a Tableau. You’ll even get an intro to the Python, R, and SQL coding needed to take your data skills to a new level. With this Dummies guide, you’ll be well on your way to becoming a priceless data jockey.
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  • 66
    Online Resource
    Online Resource
    [Erscheinungsort nicht ermittelbar] : John Wiley
    ISBN: 9781394263486 , 1394263481 , 9781394263479
    Language: English
    Pages: 1 online resource
    Series Statement: For dummies
    Parallel Title: Erscheint auch als
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Computer programming ; Python (Langage de programmation) ; Programmation (Informatique) ; computer programming
    Abstract: Python Essentials For Dummies is a quick reference to all the core concepts in Python, the multifaceted general-purpose language used for everything from building websites to creating apps. This book gets right to the point, with no excess review, wordy explanations, or fluff, making it perfect as a desk reference on the job or as a brush-up as you expand your skills in related areas. Focusing on just the essential topics you need to know to brush up or level up your Python skill, this is the reliable little book you can always turn to for answers.
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  • 67
    Online Resource
    Online Resource
    [Sebastopol, California] : O'Reilly Media, Inc.
    ISBN: 9781098171414 , 1098171411
    Language: English
    Pages: 1 online resource (5 pages)
    Edition: [First edition].
    Series Statement: Shortcuts
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Unicode (Computer character set) ; Python (Langage de programmation) ; Unicode (Jeu de caractères)
    Abstract: Build your knowledge of Python with this Shortcuts collection. Focusing on common problems involving text manipulation, many of these tasks can be solved using built-in methods of strings. More complicated operations may require regular expressions or the creation of a full-fledged parser.
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  • 68
    Online Resource
    Online Resource
    Sebastopol, CA : O'Reilly Media, Inc.
    ISBN: 9781098171575 , 1098171578
    Language: English
    Pages: 1 online resource (5 pages)
    Edition: [First edition].
    Series Statement: Shortcuts
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Python (Langage de programmation)
    Abstract: Build your knowledge of Python, the world’s favorite programming language, with this Shortcuts collection. These recipes address a range of well-known and more advanced function definitions, as well as common programming patterns for class and object definitions.
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  • 69
    Online Resource
    Online Resource
    [Sebastopol, California] : O'Reilly Media, Inc.
    ISBN: 9781098171636 , 1098171632
    Language: English
    Pages: 1 online resource (5 pages)
    Edition: [First edition].
    Series Statement: Shortcuts
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Python (Langage de programmation)
    Abstract: Build your knowledge of Python, the world’s favorite programming language, with this Shortcuts collection. These recipes address a range of well-known and more advanced function definitions, as well as common programming patterns for class and object definitions.
    Library Location Call Number Volume/Issue/Year Availability
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  • 70
    Online Resource
    Online Resource
    [Sebastopol, California] : O'Reilly Media, Inc.
    ISBN: 9781098171391 , 109817139X
    Language: English
    Pages: 1 online resource (5 pages)
    Edition: [First edition].
    Series Statement: Shortcuts
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Programming languages (Electronic computers) ; Python (Langage de programmation)
    Abstract: Build your knowledge of Python with this Shortcuts collection. Focusing on common problems involving text manipulation, many of these tasks can be solved using built-in methods of strings. More complicated operations may require regular expressions or the creation of a full-fledged parser.
    Note: Includes bibliographical references
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  • 71
    Online Resource
    Online Resource
    [Birmingham, United Kingdom] : Packt Publishing Ltd.
    ISBN: 9781836204671 , 1836204671
    Language: English
    Pages: 1 online resource (1 video file (6 hr., 45 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Data structures (Computer science) ; Python (Langage de programmation) ; Structures de données (Informatique) ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: This comprehensive course begins with fundamental concepts, introducing you to basic data structures like arrays and lists, and progressively covers more complex structures such as linked lists, stacks, queues, trees, and graphs. Each lesson is intricately designed to build upon the previous, ensuring a seamless transition from simple to complex data management techniques. As the course unfolds, you'll delve into the practical implementations and theoretical underpinnings of each data structure. We not only explain the operations of each structure but also demonstrate their real-world applications in Python, enabling you to optimize software performance and tackle programming challenges with precision. Detailed video tutorials guide you through the intricacies of data manipulation, ensuring you understand how to effectively utilize data structures in your projects. This approach not only enhances learning but also ensures you can apply these structures to solve practical, real-world problems. By the end of this course, your transformation from a beginner to a proficient Python programmer will be well underway. You'll possess the skills to handle complex data structures, making you a valuable asset in the tech industry.
    Note: Online resource; title from title details screen (O’Reilly, viewed May 14, 2024)
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  • 72
    Online Resource
    Online Resource
    [Sebastopol, California] : O'Reilly Media, Inc.
    ISBN: 9781098171407 , 1098171403
    Language: English
    Pages: 1 online resource (5 pages)
    Edition: [First edition].
    Series Statement: Shortcuts
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Unicode (Computer character set) ; Computer programming ; Python (Langage de programmation) ; Unicode (Jeu de caractères) ; Programmation (Informatique) ; computer programming
    Abstract: Build your knowledge of Python with this Shortcuts collection. Focusing on common problems involving text manipulation, many of these tasks can be solved using built-in methods of strings. More complicated operations may require regular expressions or the creation of a full-fledged parser.
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  • 73
    ISBN: 9781835468524
    Language: English
    Pages: 1 online resource (278 pages) , illustrations
    Edition: First edition.
    DDC: 006.7/6
    Keywords: Django (Electronic resource) ; Python (Computer program language) ; Web site development ; Internet programming ; Python (Langage de programmation) ; Sites Web ; Développement ; Programmation Internet
    Abstract: Are you a Django developer looking to leverage microservices to create optimized and scalable web applications? If yes, then this book is for you. With microservices, you can split an application into self-contained services, each with a specific scope running asynchronously while collectively executing processes. Written by an experienced Python developer, Hands-On Microservices with Django teaches you how to develop and deploy microservices using Django and accompanying components such as Celery and Redis. You'll start by learning the principles of microservices and message/task queues and how to design them effectively. Next, you’ll focus on building your first microservices with Django RESTful APIs (DFR) and RabbitMQ, mastering the fundamentals along the way. As you progress, you’ll get to grips with dockerizing your microservices. Later, you’ll discover how to optimize and secure them for production environments. By the end of this book, you’ll have the skills you need to design and develop production-ready Django microservices applications with DFR, Celery/RabbitMQ, Redis, and Django's cache framework.
    Note: Includes index
    Library Location Call Number Volume/Issue/Year Availability
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  • 74
    Online Resource
    Online Resource
    [Sebastopol, California] : O'Reilly Media, Inc.
    ISBN: 9781098171629 , 1098171624
    Language: English
    Pages: 1 online resource (5 pages)
    Edition: [First edition].
    Series Statement: Shortcuts
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Computer programming ; Python (Langage de programmation) ; Programmation (Informatique) ; computer programming
    Abstract: Build your knowledge of Python, the world’s favorite programming language, with this Shortcuts collection. These recipes address a range of well-known and more advanced function definitions, as well as common programming patterns for class and object definitions.
    Library Location Call Number Volume/Issue/Year Availability
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  • 75
    Online Resource
    Online Resource
    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (4 hr., 20 min.)) , sound, color.
    Edition: [First edition].
    Series Statement: Pragmatic AI labs course
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Data structures (Computer science) ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Learn Python and Pandas with O'Reilly Author Kennedy Behrman.
    Note: Online resource; title from title details screen (O’Reilly, viewed May 7, 2024)
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  • 76
    Online Resource
    Online Resource
    [Sebastopol, California] : O'Reilly Media, Inc.
    ISBN: 9781098171384 , 1098171381
    Language: English
    Pages: 1 online resource (5 pages)
    Edition: [First edition].
    Series Statement: Shortcuts
    DDC: 005.13/3
    Keywords: Python (Computer program language)
    Abstract: Build your knowledge of Python with this Shortcuts collection. Focusing on common problems involving text manipulation, many of these tasks can be solved using built-in methods of strings. More complicated operations may require regular expressions or the creation of a full-fledged parser.
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  • 77
    Online Resource
    Online Resource
    [Shelter Island, New York] : Manning Publications
    Language: English
    Pages: 1 online resource (1 video file (3 hr., 2 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Machine learning ; Python (Langage de programmation) ; Apprentissage automatique ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: This intensive program is designed for both beginners eager to dive into the world of data science and seasoned professionals looking to deepen their understanding of machine learning, deep learning, and TensorFlow's capabilities. Starting with Python—a cornerstone of modern AI development—we'll guide you through its essential features and libraries that make data manipulation and analysis a breeze. As we delve into machine learning, you'll learn the foundational algorithms and techniques, moving seamlessly from supervised to unsupervised learning, paving the way for the magic of deep learning. With TensorFlow, one of the most dynamic and widely-used deep learning frameworks, we'll uncover how to craft sophisticated neural network architectures, optimize models, and deploy AI-powered solutions. We don't just want you to learn—we aim for you to master. By the course's end, you'll not only grasp the theories but also gain hands-on experience, ensuring that you're industry ready. Whether you aspire to innovate in AI research or implement solutions in business settings, this comprehensive course promises a profound understanding, equipping you with the tools and knowledge to harness the power of Python, Machine Learning, and TensorFlow.
    Note: Online resource; title from title details screen (O’Reilly, viewed May 7, 2024)
    Library Location Call Number Volume/Issue/Year Availability
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  • 78
    Online Resource
    Online Resource
    [Place of publication not identified] : Pragmatic AI Solutions
    Language: English
    Pages: 1 online resource (1 video file (48 min.)) , sound, color.
    Edition: [First edition].
    Series Statement: Pragmatic AI labs course
    DDC: 006.3/12
    Keywords: Data mining ; Information visualization ; Computer graphics ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: This video series covers the fundamentals of working with Jupyter Notebooks and popular managed notebook platforms. It introduces the Jupyter Notebook interface, explains how to create and manipulate notebook cells, and demonstrates key features like magic commands. It also explores cloud-based notebook environments including Google Colab, AWS SageMaker, and SageMaker Studio, highlighting their unique capabilities and use cases. Through live coding examples, you'll learn to work effectively with these tools for data science and machine learning projects.
    Note: Online resource; title from title details screen (O'Reilly, viewed May 6, 2024)
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  • 79
    ISBN: 9781663735577 , 1663735573
    Language: English
    Pages: 1 online resource (1 sound file (10 hr., 15 min.))
    Edition: [First edition].
    DDC: 332.64/20285
    Keywords: Electronic trading of securities ; Deep learning (Machine learning) ; Python (Computer program language) ; Valeurs mobilières ; Commerce électronique ; Apprentissage profond ; Python (Langage de programmation) ; Audiobooks ; Livres audio
    Abstract: Deep learning is rapidly gaining momentum in the world of finance and trading. But for many professional traders, this sophisticated field has a reputation for being complex and difficult. This hands-on guide teaches you how to develop a deep learning trading model from scratch using Python, and it also helps you create and backtest trading algorithms based on machine learning and reinforcement learning. Sofien Kaabar-financial author, trading consultant, and institutional market strategist-introduces deep learning strategies that combine technical and quantitative analyses. By fusing deep learning concepts with technical analysis, this unique book presents outside-the-box ideas in the world of financial trading. This A-Z guide also includes a full introduction to technical analysis, evaluating machine learning algorithms, and algorithm optimization. This book will help you to understand and create machine learning and deep learning models; explore the details behind reinforcement learning and see how it's used in time series; understand how to interpret performance evaluation metrics; examine technical analysis and learn how it works in financial markets; create technical indicators in Python and combine them with ML models for optimization; and evaluate the models' profitability and predictability to understand their limitations and potential.
    Note: Online resource; title from title details screen (O’Reilly, viewed April 29, 2024)
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  • 80
    Online Resource
    Online Resource
    [Birmingham, United Kingdom] : Packt Publishing
    ISBN: 9781836202356 , 1836202350
    Language: English
    Pages: 1 online resource (1 video file (5 hr., 32 min.)) , sound, color.
    Edition: [First edition].
    DDC: 006.3/12
    Keywords: Big data Data processing ; Data mining ; Automatic data collection systems ; Electronic data processing ; Exploration de données (Informatique) ; Collecte automatique des données ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: Begin your Splunk journey with our comprehensive video course designed to guide you through every facet of this powerful tool. Start with a condensed history to understand why Splunk has become an essential tool for data-driven decisions. You'll dive into the components that constitute Splunk, ensuring you grasp each element's role in a successful implementation. From installing Splunk and understanding its licensing to configuring and managing data inputs, this course covers the operational spectrum. Gain deep insights into managing user roles and authentications, setting up robust data retention policies, and leveraging Splunk's advanced data transformation capabilities. By the end, you'll not only be prepared to effectively use Splunk in your organization but also to optimize its functionalities to suit your specific needs.
    Note: Online resource; title from title details screen (O’Reilly, viewed May 14, 2024)
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  • 81
    ISBN: 9781617296482 , 1617296481
    Language: English
    Pages: 1 online resource (xxvi, 523 pages) , illustrations.
    Parallel Title: Erscheint auch als
    DDC: 006.3/1
    Keywords: Deep learning (Machine learning) ; Deep learning (Machine learning) Mathematics ; Python (Computer program language) ; Apprentissage profond ; Apprentissage profond ; Mathématiques ; Python (Langage de programmation) ; Deep learning (Machine learning) ; Python (Computer program language)
    Abstract: Discover what's going on inside the black box! To work with deep learning you'll have to choose the right model, train it, preprocess your data, evaluate performance and accuracy, and deal with uncertainty and variability in the outputs of a deployed solution. This book takes you systematically through the core mathematical concepts, linear algebra, and Bayesian inference, all from a deep learning perspective. Math and archtectures of deep learning teaches the math, theory, and programming principles of deep learning models laid out side by side, and then puts them into practice with well-annotated Python code. You'll progrress from algebra, calculus, and statistics all the way to state-of-the-art DL architectures taken from the latest research.
    Note: Includes index. - Description based on print version record
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  • 82
    Online Resource
    Online Resource
    [Place of publication not identified] : Pearson
    ISBN: 9780135359051 , 0135359058
    Language: English
    Pages: 1 online resource (1 video file (8 hr., 2 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.1/14
    Keywords: Functional programming (Computer science) ; JavaScript (Computer program language) ; Python (Computer program language) ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Functional Programming is a revolutionary way of writing code that’s rapidly gaining traction in the world of software development. While Object-Oriented Programming is still the most popular programming paradigm, there are a number of problems that come about when using it—hard-to-find bugs, tightly coupled code, and it’s difficult to scale. Functional programming allows us to solve or avoid these problems by taking a different approach to writing software. Functional Programming Projects with JavaScript teaches all about the core concepts of Functional Programming and how to apply them in JavaScript, mix of screen casting, slides, and coding. Basic functional concepts lead to first class functions, which leads to working with arrays and objects and then advanced functional concepts. Functional Programming Projects with Python 3 is about the core concepts of Functional Programming and how to apply them in Python, through a mix of screen casting, slides, and coding. It also covers basic functional concepts that lead to first class functions, which leads to working with arrays and objects and then advanced functional concepts.
    Note: Online resource; title from title details screen (O’Reilly, viewed May 7, 2024)
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  • 83
    Online Resource
    Online Resource
    Shelter Island, NY : Manning Publications
    Language: English
    Pages: 1 online resource (1 video file (3 hr., 52 min.)) , sound, color.
    Edition: [First edition].
    DDC: 006.3/12
    Keywords: Data mining ; Python (Computer program language) ; Exploration de données (Informatique) ; Python (Langage de programmation) ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: Harness the potential of extracting web data with our detailed course on Web Scraping using Beautiful Soup in Python. Begin your journey with an introduction to the basics of web scraping. Learn why Python and its robust library, Beautiful Soup, are favorites among developers and data enthusiasts. Immerse yourself in the details of HTML structures, learning to identify and navigate through various HTML tags and mastering CSS selectors to precisely extract the data you need. Take advantage of the Requests library for easy and effective management of HTTP requests, simplifying the process of web content retrieval. Advance your skills with hands-on experience in Beautiful Soup, covering everything from fundamental parsing to sophisticated data extraction methods. Practical application is key. Our course offers numerous real-world projects, giving you the chance to apply your skills in different settings, including tracking eBay prices, extracting top hits from Billboard, sourcing movie recommendations from IMDB, and keeping an eye on Bitcoin prices. Complete this course with the ability to effortlessly scrape web data and turn it into valuable insights.
    Note: Online resource; title from title details screen (O'Reilly, viewed May 7, 2024)
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  • 84
    ISBN: 9781803244051 , 1803244054 , 9781803232164
    Language: English
    Pages: 1 online resource (198 p.)
    Edition: 1st edition.
    Parallel Title: Erscheint auch als Shah, Krishna Kibana 8.x - a Quick Start Guide to Data Analysis
    DDC: 001.4/226
    Keywords: Information visualization ; Data mining ; Visualisation de l'information ; Exploration de données (Informatique)
    Abstract: Uncover valuable business insights by leveraging the power of Kibana to navigate and interpret datasets for improved decision making Key Features Gain profound understanding of the end-to-end workings of Kibana Explore the powerful administration features in Kibana 8.x for managing and supporting data ingestion pipelines Build your own analytics and visualization solution from scratch Purchase of the print or Kindle book includes a free PDF eBook Book Description Unleash the full potential of Kibana--an indispensable tool for data analysts to seamlessly explore vast datasets, uncover key insights, identify trends and anomalies, and share results. This book guides you through its user-friendly interface, interactive visualizations, and robust features, including real-time data monitoring and advanced analytics, showing you how Kibana revolutionizes your approach to navigating and analyzing complex datasets. Starting with the foundational steps of installing, configuring, and running Kibana, this book progresses systematically to explain the search and data visualization capabilities for data stored in the Elasticsearch cluster. You'll then delve into the practical details of creating data views and optimizing spaces to better organize the analysis environment. As you advance, you'll get to grips with using the discover interface and learn how to build different types of extensive visualizations using Lens. By the end of this book, you'll have a complete understanding of how Kibana works, helping you leverage its capabilities to build an analytics and visualization solution from scratch for your data-driven use case. What you will learn Create visualizations using the Visualize interface in Kibana Build shareable search dashboards to drill down and perform advanced analysis and reporting Search data to make correlations and identify and explain trends Embed dashboards, share links, and export PNG, PDF, or CSV files and send as an attachment Configure and tweak advanced settings to best manage saved objects in Kibana Implement several types of aggregations working behind the scenes of extensive visualizations Who this book is for If you're a data analyst or a data engineer, this book is for you. It's also a useful resource to database administrators, analysts, and business users looking to build a foundation in creating intuitive dashboards using Kibana 8.x and data analysis techniques for improved decision making. Foundational knowledge of Elasticsearch fundamentals will provide an added advantage.
    Note: Description based upon print version of record. - Chapter 10: Query DSL and Management through Kibana
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  • 85
    Online Resource
    Online Resource
    [Birmingham, United Kingdom] : Packt Publishing
    ISBN: 9781836204312 , 1836204310
    Language: English
    Pages: 1 online resource (1 video file (8 hr., 18 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Computer programming ; Coding theory ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: "Using Community Code" is designed to empower developers by teaching them how to effectively use and manage community-written code within their Python projects. The course begins with an introduction to the concept of community code, exploring popular repositories and libraries that help solve common programming challenges. We then delve into practical skills, such as installing and managing packages with pip, creating and handling virtual environments, and mastering environment management tools like pipenv and conda. Throughout the course, we provide hands-on demonstrations on how to integrate these tools into your development workflow, ensuring that you can apply what you learn directly to your projects. By the end of the series, you will not only be proficient in managing Python environments but also in optimizing your development process by utilizing powerful community-driven solutions.
    Note: Online resource; title from title details screen (O’Reilly, viewed May 7, 2024)
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  • 86
    Online Resource
    Online Resource
    [Birmingham, United Kingdom] : Packt Publishing Ltd.
    ISBN: 9781836206330 , 183620633X
    Language: English
    Pages: 1 online resource (1 video file (9 hr., 21 min.)) , sound, color.
    Edition: [First edition].
    DDC: 006.3
    Keywords: Artificial intelligence ; Natural language processing (Computer science) ; Python (Computer program language) ; Machine learning ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: Delve into the expansive field of Natural Language Processing (NLP) through a structured journey that starts with the basics and advances to complex real-world applications. Begin by setting up your development environment, understanding essential tools, and getting familiar with the course resources. As you progress, you will explore foundational NLP techniques like text classification and sentiment analysis, and learn to manipulate and analyze text data effectively. The course emphasizes practical application, guiding you through the creation and management of vector databases, and the implementation of state-of-the-art models like Huggingface's Transformers. The curriculum includes detailed sections on innovative NLP strategies such as prompt engineering and chain-of-thought reasoning, equipping you with the skills to tackle advanced problems in text processing. Each concept is broken down into comprehensible modules, ensuring you can build and fine-tune machine learning models that enhance the capabilities of NLP applications. By the end of this course, you'll have mastered the tools and techniques to not only execute complex NLP tasks but also to implement these solutions effectively in your professional projects, contributing to your growth as a data-driven decision-maker in the tech industry.
    Note: Online resource; title from title details screen (O’Reilly, viewed May 7, 2024)
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  • 87
    ISBN: 9781805121916 , 180512191X , 9781805120100
    Language: English
    Pages: 1 online resource
    Edition: 1st edition.
    Parallel Title: Erscheint auch als
    DDC: 006.3/2
    Keywords: Neural networks (Computer science) ; Machine learning ; Python (Computer program language) ; Réseaux neuronaux (Informatique) ; Apprentissage automatique ; Python (Langage de programmation)
    Abstract: Dramatically accelerate the building process of complex models using PyTorch to extract the best performance from any computing environment Key Features Reduce the model-building time by applying optimization techniques and approaches Harness the computing power of multiple devices and machines to boost the training process Focus on model quality by quickly evaluating different model configurations Purchase of the print or Kindle book includes a free PDF eBook Book Description Penned by an expert in High-Performance Computing (HPC) with over 25 years of experience, this book is your guide to enhancing the performance of model training using PyTorch, one of the most widely adopted machine learning frameworks. You'll start by understanding how model complexity impacts training time before discovering distinct levels of performance tuning to expedite the training process. You'll also learn how to use a new PyTorch feature to compile the model and train it faster, alongside learning how to benefit from specialized libraries to optimize the training process on the CPU. As you progress, you'll gain insights into building an efficient data pipeline to keep accelerators occupied during the entire training execution and explore strategies for reducing model complexity and adopting mixed precision to minimize computing time and memory consumption. The book will get you acquainted with distributed training and show you how to use PyTorch to harness the computing power of multicore systems and multi-GPU environments available on single or multiple machines. By the end of this book, you'll be equipped with a suite of techniques, approaches, and strategies to speed up training , so you can focus on what really matters--building stunning models! What you will learn Compile the model to train it faster Use specialized libraries to optimize the training on the CPU Build a data pipeline to boost GPU execution Simplify the model through pruning and compression techniques Adopt automatic mixed precision without penalizing the model's accuracy Distribute the training step across multiple machines and devices Who this book is for This book is for intermediate-level data scientists who want to learn how to leverage PyTorch to speed up the training process of their machine learning models by employing a set of optimization strategies and techniques. To make the most of this book, familiarity with basic concepts of machine learning, PyTorch, and Python is essential. However, there is no obligation to have a prior understanding of distributed computing, accelerators, or multicore processors.
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  • 88
    Online Resource
    Online Resource
    [Shelter Island, New York] : Manning Publications
    Language: English
    Pages: 1 online resource (1 video file (6 hr., 7 min.)) , sound, color.
    Edition: [First edition]
    DDC: 629.8/92
    Keywords: Robotics ; Python (Computer program language) ; Raspberry Pi (Computer) ; Robotique ; Python (Langage de programmation) ; Raspberry Pi (Ordinateur) ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: Build Your Own Robot is a project-based guide that takes you from spinning your first DC motor to programming a mobile robot that you can control from your phone or computer. You’ll write simple Python code to help your new friend spin, move, and find its way. You’ll even teach it to track faces and fetch snacks. Plus, a helpful hardware purchasing guide makes it easy to find exactly what you need to get started!
    Note: Online resource; title from title details screen (O’Reilly, viewed May 6, 2024)
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  • 89
    Online Resource
    Online Resource
    [Birmingham, United Kingdom] : Packt Publishing
    ISBN: 9781836201892 , 1836201893
    Language: English
    Pages: 1 online resource (1 video file (8 hr., 43 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.7
    Keywords: Big data ; Data mining ; Exploration de données (Informatique) ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: Our "Survey of Data Science" course provides a deep dive into the world of data analysis and modeling, equipping learners with the skills to transform raw data into insightful decisions. Starting with an introduction to data scientists' roles and activities, the course progresses through data exploration and analysis. You will learn about the importance of data hygiene, statistical foundations, and the power of visualization to communicate data-driven insights effectively. As the course unfolds, it covers complex topics such as handling unstructured data, building associative rules, decision trees, and regression models, and delves into sophisticated areas like neural networks and natural language processing. The Lambda architecture section will illuminate real-time and batch data processing, essential for handling big data scenarios in professional settings. The course not only provides technical skills but also emphasizes practical application, preparing participants to apply their knowledge in real-world situations. This journey will equip you with the expertise to navigate the challenges of modern data science, making you an asset in various industry roles.
    Note: Online resource; title from title details screen (O'Reilly, viewed May 7, 2024)
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  • 90
    Online Resource
    Online Resource
    [Place of publication not identified] : Pearson
    ISBN: 9780135360866 , 0135360862
    Language: English
    Pages: 1 online resource (1 video file (7 hr., 44 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Python (Langage de programmation) ; Instructional films ; Nonfiction films ; Internet videos ; Films de formation ; Films autres que de fiction ; Vidéos sur Internet
    Abstract: Python has risen to popularity as one of the most versatile and beginner-friendly programming languages. Its simplicity, readability, and extensive libraries make it a powerful language for a wide variety of different domains. It’s widely used in web development, data analysis, scientific computing, artificial intelligence, and automation. Python’s versatility and large community support make it an excellent language to kickstart your programming journey.
    Note: Online resource; title from title details screen (O’Reilly, viewed May 7, 2024)
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  • 91
    Online Resource
    Online Resource
    [Sebastopol, California] : O'Reilly Media, Inc.
    ISBN: 9781098171582 , 1098171586
    Language: English
    Pages: 1 online resource (5 pages)
    Edition: [First edition].
    Series Statement: Shortcuts
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Python (Langage de programmation)
    Abstract: Build your knowledge of Python, the worlds favorite programming language, with this Shortcuts collection. These recipes address a range of well-known and more advanced function definitions, as well as common programming patterns for class and object definitions.
    Note: Includes bibliographical references
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  • 92
    ISBN: 9781804615546 , 1804615544
    Language: English
    Pages: 1 online resource (345 p.)
    Edition: 1st edition.
    DDC: 006.3/12
    Keywords: Data mining ; Data mining Computer programs
    Abstract: Seamlessly integrate the Python and R programming languages with spreadsheet-based data analysis to maximize productivity Key Features Perform advanced data analysis and visualization techniques with R and Python on Excel data Use exploratory data analysis and pivot table analysis for deeper insights into your data Integrate R and Python code directly into Excel using VBA or API endpoints Purchase of the print or Kindle book includes a free PDF eBook Book Description For businesses, data analysis and visualization are crucial for informed decision-making; however, Excel's limitations can make these tasks time-consuming and challenging. Extending Excel with Python and R is a game changer resource written by experts Steven Sanderson, the author of the healthyverse suite of R packages, and David Kun, co-founder of Functional Analytics, the company behind the ownR platform engineering solution for R, Python, and other data science languages. This comprehensive guide transforms the way you work with spreadsheet-based data by integrating Python and R with Excel to automate tasks, execute statistical analysis, and create powerful visualizations. Working through the chapters, you'll find out how to perform exploratory data analysis, time series analysis, and even integrate APIs for maximum efficiency. Whether you're a beginner or an expert, this book has everything you need to unlock Excel's full potential and take your data analysis skills to the next level. By the end of this book, you'll be able to import data from Excel, manipulate it in R or Python, and perform the data analysis tasks in your preferred framework while pushing the results back to Excel for sharing with others as needed. What you will learn Read and write Excel files with R and Python libraries Automate Excel tasks with R and Python scripts Use R and Python to execute Excel VBA macros Format Excel sheets using R and Python packages Create graphs with ggplot2 and Matplotlib in Excel Analyze Excel data with statistical methods and time series analysis Explore various methods to call R and Python functions from Excel Who this book is for If you're a data analyst or data scientist, or a quants, actuaries, or data practitioner looking to enhance your Excel skills and expand your data analysis capabilities with R and Python, this book is for you. It provides a comprehensive introduction to the topics covered, making it suitable for both beginners and intermediate learners. A basic understanding of Excel, Python, and R is all you need to get started.
    Note: Description based upon print version of record. - Cell formatting
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  • 93
    Online Resource
    Online Resource
    Frechen : mitp Verlag
    ISBN: 9783747506578 , 3747506577
    Language: German
    Pages: 1 online resource (208 pages) , illustrations
    Edition: [1. Auflage].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Application software Development
    Abstract: Kinderleicht programmieren lernen? Kein Problem! Mit diesem Buch lernst du Schritt für Schritt und anhand zahlreicher Beispiele die Grundlagen der Programmiersprache Python. Viele Bilder und kurze anschauliche Texte erleichtern dir das Verständnis. Alle Beispielprogramme werden ganz genau erklärt. Dich erwarten spannende Projekte wie zum Beispiel das Programmieren eines digitalen Assistenten zum Gedichteschreiben, ein Planeten-Ratespiel oder ein Programm zum Verwalten deiner Notizen. Du lernst, wie du Benutzungsoberflächen mit Bildern und Schaltflächen erstellst und wie du mit Daten aus dem Internet das Wetter vorhersagen kannst. Challenges mit Lösungen testen dein Wissen und fordern dich heraus, selbst kreativ zu werden. Damit hast du alles, was du brauchst, um deine eigenen Ideen mit Python umzusetzen und in der Welt der Programmierung durchzustarten.
    Note: Includes index
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  • 94
    ISBN: 9781484287545 , 1484287541
    Language: English
    Pages: 1 online resource (716 pages) , illustrations
    Edition: Second edition.
    Parallel Title: Erscheint auch als
    Keywords: Decision making Data processing ; Business planning Data processing ; R (Computer program language) ; Python (Computer program language) ; Electronic books
    Abstract: This book illustrates how data can be useful in solving business problems. It explores various analytics techniques for using data to discover hidden patterns and relationships, predict future outcomes, optimize efficiency and improve the performance of organizations. You’ll learn how to analyze data by applying concepts of statistics, probability theory, and linear algebra. In this new edition, both R and Python are used to demonstrate these analyses. Practical Business Analytics Using R and Python also features new chapters covering databases, SQL, Neural networks, Text Analytics, and Natural Language Processing. Part one begins with an introduction to analytics, the foundations required to perform data analytics, and explains different analytics terms and concepts such as databases and SQL, basic statistics, probability theory, and data exploration. Part two introduces predictive models using statistical machine learning and discusses concepts like regression, classification, and neural networks. Part three covers two of the most popular unsupervised learning techniques, clustering and association mining, as well as text mining and natural language processing (NLP). The book concludes with an overview of big data analytics, R and Python essentials for analytics including libraries such as pandas and NumPy. Upon completing this book, you will understand how to improve business outcomes by leveraging R and Python for data analytics.
    Note: Includes bibliographical references and index
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  • 95
    Online Resource
    Online Resource
    [Place of publication not identified] : Addison-Wesley Professional
    ISBN: 9780138050764 , 0138050767
    Language: English
    Pages: 1 online resource (1 video file (7 hr., 31 min.)) , sound, color.
    Edition: [First edition].
    Series Statement: Live lessons
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Computer programming ; Computer programming ; Python (Computer program language) ; Instructional films ; Internet videos ; Nonfiction films ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: 7.5 Hours of Video Instruction In Learn Enough Python to Be Dangerous: A Tutorial Introduction to Programming with Python, renowned instructor Michael Hartl teaches you to write practical and modern programs using the elegant and powerful Python programming language. Overview Programmers love Python for its clean syntax, flexible data types, a wealth of useful libraries, and a powerful and elegant design that supports multiple styles of programming. That's why it is popular for varied uses such as scripting, web development, and data science. You'll love Python too, but you don't need to learn "everything" about it, just how to use it efficiently to solve real problems. Best-selling author Michael Hartl gets you started writing practical and modern Python programs as fast as possible, with a focus on the real tools used every day by software developers. You'll learn how to use Python interactively, write shell scripts in it, use Python and a web framework to make simple dynamic web applications, and use Python libraries to do data science. Even if you're new to programming, Hartl helps you quickly build technical sophistication as you gain a solid understanding of object-oriented and functional programming, develop and publish a Python web application with the Flask framework. Focused exercises help you internalize what matters, without wasting time on details pros don't care about. Soon, it'll be like you were born knowing this stuff--and you'll be suddenly, seriously dangerous. About the Instructor Michael Hartl is the creator of the Python on Rails Tutorial, one of the leading introductions to web development, and is cofounder and principal author at Learn Enough. Previously, he was a physics instructor at the California Institute of Technology (Caltech), where he received a Lifetime Achievement Award for Excellence in Teaching. He is a graduate of Harvard College, has a Ph.D. in Physics from Caltech, and is an alumnus of the Y Combinator entrepreneur program. Skill Level Beginner to intermediate Learn How To Create a simple "hello, world" program using several different techniques Deploy a simple dynamic Python application to the web Use strings, arrays, and other native objects Define functions Use Python for functional and object-oriented programming Utilize test-driven development Write a shell script Develop a full Python web application for detecting palindromes Who Should Take This Course New and experienced developers looking for a practical introduction to Python. Course Requirements The only prerequisites are a familiarity with basic developer tools (command line, text editor, and Git) and beginning HTML Some programming experience is useful but not required Lesson Descriptions Lesson 1: Hello World! Lesson 1 begins at the beginning by having you create four simple "hello, world" programs using several different techniques. The main purpose of the "hello, world" is to make sure your system is correctly configured to execute the simple program that prints the string "hello, world!" to the screen. You start by writing a series of programs to display a greeting at a command line terminal, first in a REPL, then from a file, and then from a shell script. Finally, you write and deploy a simple proof-of-concept web application using the Flask web framework. Lesson 2: Strings Lesson 2 covers strings, probably the most important data structure on the Web since Web pages ultimately consist of strings and characters sent to and from the browser. Many other kinds of programs require string manipulation as well. As a result, strings make a great place to start your Python programming journey. The lesson starts with what strings are and how to create them. You then learn how to join, or concatenate, multiple string into a single string. Then you learn how to insert or interpolate one string into another. Next you learn how to print strings to the screen from the terminal window. As part of this, you see your first examples of Python Boolean variables and control flow. Finally, you learn how to iterate over strings with for loops, enabling you to access strings one character at a time. Lesson 3 : Lists In Lesson 2, you learned that strings can be thought of sequences of characters in a particular order. In Lesson 3, you learn about the list data type, which is the general Python container for arbitrary elements in a particular order. You start by explicitly connecting strings and lists via the string split method, and then you learn about various list methods throughout the rest of the lesson. After learning to split strings, you learn how to access elements in the resulting list, discovering that the same syntax works on strings, further deepening the connection between the two data types. Next you learn a variety of additional list methods beginning with selecting both single elements and multiple elements at once using list slicing, including the useful range datatype, and a clever technique using negative indices to select the last element in a list. Then you learn how to sort lists, which, if you have ever written a sorting algorithm by hand, you will find Python makes it ridiculously easy. You also learn how to reverse lists, a capability you will put to good use later on in the tutorial when learning to detect palindromes. Next you will learn how to add and remove list elements using append and pop. You then learn how to undo a string split using a list join, which includes an introduction to an important technique known as generator comprehension. Next, you learn how to iterate through lists using the same kind of for loop covered in Lesson in 2, which is valuable preparation for more advanced techniques covered in Lesson 6. Finally, you learn about two data types closely related to lists: tuples, which are essentially immutable lists, and sets, which can be thought of as a list of elements where repeat elements are ignored and the order doesn't matter. Lesson 4: Other Native Objects Now that we have taken a look at strings and arrays, Lesson 4 continues with a tour of some other important Python objects, which will give you a chance to learn about math, dates, regular expressions, and dictionaries. Like most programming languages, Python supports a large number of mathematical operations right out of the box, such as addition, subtraction, multiplication, and division. It also includes a math library, so you learn about more advanced operations such as logarithms and trigonometric functions. You also see an example of a personal triumph of mine, the inclusion of the circle constant Ï⁴ (tau), to find us the ratio of a circle's circumference to its radius, which Michael first proposed in 2010 and which was added to Python's standard math library in 2017. You also learn how to deal with times and dates in Python, such as getting the year, the day, or the exact time. Next you get an introduction in the powerful subject of regular expressions, which were discussed briefly in Learn Enough Developer Tools to Be Dangerous in the context of text editors and the grep command. Often called regexes for short, regular expressions are a powerful mini-language for matching patterns in text. You learn how to use regexes to quickly search strings for things like five digits in a row, thereby matching standard United States ZIP codes. The lesson ends with an introduction to dictionaries in Python. You use such objects, often referred to as hashes or associative arrays in other languages, are defined by key-value pairs, and in many ways behave like lists with strings, or sometimes other objects, instead of integers as indices. You apply this important object type to write your first substantial Python program, a shell script to count the unique words in a text. Lesson 5: Functions and Iterators So far in this tutorial, Python functions have been mentioned repeatedly, and and in Lesson 5 you finally learn to define functions of your own. The resulting ability gives us greater flexibility as programmers. We begin your study of functions in the read-eval-print loop, that is, the REPL, and then you learn how to put your function definitions in a file for use in a simple Flask web application. The lesson ends with a discussion of iterators, which are a powerful Python object type that represents a stream of data. The lesson pays particular attention to generators, probably the most common type of Python iterator. You will use a generator to make a first definition of an ispalindrome function, to see if a string is the same forward and backward. Lesson 6: Functional Programming Having learned how to define functions and apply them in a couple of different contexts. In Lesson 6, you take your programming to the next level by learning the basics of functional programming, a style of programming that emphasizes, you guessed it, functions. As you will see, functional programming in Python frequently employs a powerful and very Pythonic class of techn...
    Note: Online resource; title from title details screen (O'Reilly, viewed March 21, 2023)
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  • 96
    Online Resource
    Online Resource
    Heidelberg : dpunkt
    Language: German
    Pages: 1 online resource (318 pages) , illustrations
    Edition: 1. Auflage.
    DDC: 005.13/3
    Keywords: Python (Computer program language)
    Abstract: Dieses Buch ist für vielbeschäftigte Programmierer:innen, die eine knappe und dennoch gut verständliche Einführung in Python als immer populärer werdende Programmiersprache suchen. Python lernen – kurz & gut bietet einen unterhaltsamen Einstieg und informiert Sie über viele Python-Bestandteile, die Ihnen helfen werden, schnell durchzustarten:- Installation von Python- Schnelleinstieg in die wichtigsten Aspekte- Basisbausteine wie Strings, Enums, Zufallszahlen, Fallunterscheidungen und Schleifen- Klassen und objektorientierte Programmierung- Datencontainer wie Listen, Mengen und Tupel- Fortgeschrittene Themen zu Collections wie Iteratoren, Generatoren, Slicing, Sortierungen und Comprehensions- Datumsverarbeitung inklusive Berechnungen- Dateiverarbeitung und JSON sowie Behandlung von FehlernTrotz seines kompakten Formats liefert dieses Buch eine fundierte Einführung und eine Fülle an leicht nachvollziehbaren Beispielen, die zum Experimentieren einladen. Es unterstützt Sie optimal dabei, Ihre Python-Kenntnisse auf- und auszubauen. Insbesondere wenn Sie bereits ein wenig mit z.B. Java oder C++ vertraut sind, ist dieses Buch die ideale Wahl, um solide in Python einzusteigen.
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  • 97
    ISBN: 9781837633517 , 1837633517 , 9781837637553
    Language: English
    Pages: 1 online resource (587 p.)
    Edition: 3rd ed.
    Series Statement: Expert insight
    DDC: 005.8
    Keywords: Python (Computer program language) ; Computer security ; Computer networks Security measures ; HTTP (Computer network protocol) Programming ; Electronic books
    Abstract: Python’s latest updates add numerous libraries that can be used to perform critical security-related missions, including detecting vulnerabilities in web applications, taking care of attacks, and helping to build secure and robust networks that are resilient to them. This fully updated third edition will show you how to make the most of them and improve your security posture. The first part of this book will walk you through Python scripts and libraries that you’ll use throughout the book. Next, you’ll dive deep into the core networking tasks where you will learn how to check a network’s vulnerability using Python security scripting and understand how to check for vulnerabilities in your network – including tasks related to packet sniffing. You’ll also learn how to achieve endpoint protection by leveraging Python packages along with writing forensics scripts. The next part of the book will show you a variety of modern techniques, libraries, and frameworks from the Python ecosystem that will help you extract data from servers and analyze the security in web applications. You’ll take your first steps in extracting data from a domain using OSINT tools and using Python tools to perform forensics tasks. By the end of this book, you will be able to make the most of Python to test the security of your network and applications.
    Note: Description based upon print version of record. - Implementing secure sockets with the TLS and SSL modules. - Includes bibliographical references and index
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  • 98
    Online Resource
    Online Resource
    [Place of publication not identified] : Manning Publications
    Language: English
    Pages: 1 online resource (1 video file (6 hr., 1 min.)) , sound, color.
    Edition: [First edition].
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Machine learning ; Instructional films ; Nonfiction films ; Internet videos
    Abstract: This A to Z course introduces newcomers to the world of data science and teaches the fundamental skills for using machine learning and artificial intelligence (AI) to glean meaning and insights from data. It covers Python's data types and shows how to use the must-have Python data science libraries, including Pandas for data analysis and Matplotlib for creating visuals of the results. Once you understand how to format and clean your data and perform exploratory data analysis, we move to the machine learning side. Here, we introduce you to supervised vs unsupervised learning, as well as the core algorithms, including simple and multiple linear regression. We finish up with a deep dive into a recommender system for movies, and a chance to put together all your new skills and knowledge. Each topic is described in plain English, and the course does its best to avoid mathematical notations and jargon. Once you have access to the source code, you can experiment with it and improve upon it, learning and applying these algorithms in the real world. The data science field is lucrative and growing. This course will introduce you to all the foundational skills that a data scientist must have. If you have no background in statistics, don't let that stop you from enrolling in this course!.
    Note: Online resource; title from title details screen (O'Reilly, viewed June 13, 2023)
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  • 99
    ISBN: 9788383223247 , 8383223242
    Language: Polish
    Pages: 1 online resource (504 pages)
    Edition: Wydanie III.
    Uniform Title: Python for data analysis
    DDC: 005.13/3
    Keywords: Python (Computer program language) ; Programming languages (Electronic computers) ; Data mining ; Data mining ; Programming languages (Electronic computers) ; Python (Computer program language)
    Abstract: Wprawny analityk danych potrafi z nich uzyskać wiedzę ułatwiającą podejmowanie trafnych decyzji. Od kilku lat można do tego używać nowoczesnych narzędzi Pythona, które zbudowano specjalnie do tego celu. Praca z nimi nie wymaga głębokiej znajomości statystyki czy algebry. Aby cieszyć się uzyskanymi rezultatami, wystarczy się wprawić w stosowaniu kilku pakietów i środowisk Pythona. Ta książka jest trzecim, starannie zaktualizowanym wydaniem wyczerpującego przewodnika po narzędziach analitycznych Pythona. Uwzględnia Pythona 3.0 i bibliotekę̜ pandas 1.4. Została napisana w przystępny sposób, a poszczególne zagadnienia bogato zilustrowano przykładami, studiami rzeczywistych przypadków i fragmentami kodu. W trakcie lektury nauczysz się korzystać z możliwości oferowanych przez pakiety pandas i NumPy, a także środowiska IPython i Jupyter. Nie zabrakło wskazówek dotyczących używania uniwersalnych narzędzi przeznaczonych do ładowania, czyszczenia, przekształcania i łączenia zbiorów danych. Pozycję docenią analitycy zamierzający zacząć pracę w Pythonie, jak również programiści Pythona, którzy chcą się zająć analizą danych i obliczeniami naukowymi.
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  • 100
    ISBN: 9783747506721 , 3747506720
    Language: German
    Pages: 1 online resource (304 pages) , illustrations
    Edition: 4. Auflage.
    Series Statement: Let's play
    DDC: 794.8
    Keywords: Minecraft (Game) Handbooks, manuals, etc ; Video games Handbooks, manuals, etc ; Adventure video games Handbooks, manuals, etc ; Python (Computer program language) ; Minecraft (Game) ; Python (Computer program language) ; Video games ; Handbooks and manuals
    Abstract: Du spielst schon lange Minecraft und denkst, du hast schon alles gesehen? Kennst du schon das Feuerschwert, den Enderbogen oder den Spielmodus »Schneeballschlacht«? Du willst auf Knopfdruck Türme, Mauern oder sogar ganze Häuser bauen? Vollautomatisch auf Geschehnisse in der Spielwelt reagieren? Mit eigenen Plugins kannst du all das und noch viel mehr entdecken und ganz nebenbei auch noch programmieren lernen. Python ist für Programmiereinsteiger besonders leicht zu lernen. Daniel Braun zeigt dir, wie du mit Python und Bukkit oder Spigot Erweiterungen für Minecraft programmierst, sogenannte Plugins, die du dann zusammen mit deinen Freunden auf deinem eigenen Minecraft-Server ausprobieren kannst. Dafür sind keine Vorkenntnisse erforderlich, du lernst alles von Anfang an. Nach dem Programmieren einfacher Chat-Befehle wirst du coole Plugins zum Bauen erstellen, so dass mit einem einzigen Befehl sofort z.B. ein fertiges Haus oder eine Kugel vor dir steht. Außerdem erfährst du, wie deine Plugins automatisch auf Geschehnisse in der Spielwelt reagieren können. Du kannst auch eigene Crafting-Rezepte entwerfen, um z.B. mächtige neue Waffen zu kreieren wie das Feuerschwert, das alles in Brand setzt, worauf es trifft. Am Ende lernst du sogar, wie du eigene Spielmodi entwickeln kannst, also ein Spiel im Spiel. Ob eine Schneeballschlacht mit Highscore-Liste oder ein Wettsammeln mit Belohnung für den Sieger, hier ist jede Menge Spaß garantiert. Für das alles brauchst du keine Vorkenntnisse, nur Spaß am Programmieren. Es beginnt mit ganz einfachen Beispielen, aber mit jedem Kapitel lernst du mehr Möglichkeiten kennen, um Minecraft nach deinen Wünschen anzupassen. Am Ende kannst du richtig in Python programmieren und deiner Kreativität sind keine Grenzen mehr gesetzt, um deine eigene Minecraft-Welt zu erschaffen.
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