Introduces an assortment of powerful command line utilities that can be combined to create simple, yet powerful shell scripts for processing datasets. The code samples and scripts use the bash shell, and typically involve small datasets so you can focus on understanding the features of grep, sed, and awk. Companion files with code are available for downloading from the publisher.

This book is intended primarily for those who plan to become data scientists as well as anyone who needs to perform data cleaning tasks. It contains a variety of features of NumPy and Pandas and how to create databases and tables in MySQL. Chapter 7 covers many data wrangling tasks using Python scripts and awk-based shell scripts. Companion files with code are available for downloading from the publisher. FEATURES: Provides the reader with basic Python 3, Java, and Pandas programming concepts, and an introduction to awk. Includes a chapter on RDBMs and SQL. Companion files with code.

As part of the best-selling Pocket Primer series, this book is designed to present the fundamentals of data structures using Python. Data structures provide a means to managing huge amounts of information such as large databases and the ability to use search and sort algorithms effectively. It is intended to be a fast-paced introduction to the core concepts of Python and data structures, illustrated with numerous code samples. Companion files with source code are available for downloading.

This book is for developers who are looking for an overview of basic concepts in Natural Language Processing using R. It casts a wide net of techniques to help developers who have a range of technical backgrounds. Numerous code samples and listings are included to support myriad topics. The final chapter presents the Transformer Architecture, BERT-based models, and the GPT family of models, all of which were developed during the past three years. Companion files with source code and figures are included. Features Covers extensive topics related to natural language processing using R Features companion files with source code and figures from the book

Houston, we have a problem... Flash cannot run on iPhone. Good news, though...Flash can and will run on Android Android will give you what you need to continue building cool and fresh Flash-based Apps for mobile devices, smartphones, and more. Pro Android Flash is the definitive guide to building Flash and other rich Internet apps (RIAs) on the Android platform. It covers the most popular RIA frameworks for Android developers - Flex and JavaFX - and shows you how to build rich, immersive user experiences on both Android smartphones and tablets. You'll learn how to incorporate multimedia, animation, and special effects into your apps for maximum visual appeal. You'll also cover advanced topics, including input methods, hardware inputs, deployment, and performance optimization.What you'll learn * Deployment of Flash, Flex, and JavaFX to Android * How to take your desktop RIAs and adapt them for mobile devices * How to integrate hardware inputs from the camera, GPS, compass, and accelerometer * How to build an immersive user interface with audio and video assets * How to integrate styling and artifact s from a professional designer * Best practices for mobile performance tuning and optimization Who this book is for This book is intended for developers who are looking to build rich Internet applications (RIAs) for the Android platform, especially Flash, Flex, and JavaFX.

This book is intended for those who plan to become data scientists as well as anyone who needs to perform data cleaning tasks using Pandas and NumPy. It contains a variety of code samples and features of NumPy and Pandas, and how to write regular expressions. Chapter 3 includes fundamental statistical concepts and Chapter 7 covers data visualization with Matplotlib and Seaborn. Companion files with code are available for downloading from the publisher.

This book is for developers who are looking for an introduction to basic concepts in NLP and machine learning. Numerous code samples and listings are included to support myriad topics. The first two chapters contain introductory material for NumPy and Pandas, followed by chapters on NLP concepts, algorithms and toolkits, machine learning, and NLP applications. The final chapters include examples of NLP tasks using TF2 and Keras, the Transformer architecture, BERT-based models, and the GPT family of models. The appendices contain introductory material (including Python code samples) for various topics, including data and statistics, Python3, regular expressions, Keras, TF2, Matplotlib and Seaborn. Companion files with source code and figures are included. FEATURES * Covers extensive topics related to natural language processing and machine learning * Includes separate appendices on data and statistics, regular expressions, data visualization, Python, Keras, TF2, and more * Features companion files with source code and color figures from the book

This book is for developers who are looking for an overview of basic concepts in Natural Language Processing. It casts a wide net of techniques to help developers who have a range of technical backgrounds. Numerous code samples and listings are included to support myriad topics. The first chapter shows you various details of managing data that are relevant for NLP. The next pair of chapters contain NLP concepts, followed by another pair of chapters with Python code samples to illustrate those NLP concepts. Chapter 6 explores applications, e.g., sentiment analysis, recommender systems, COVID-19 analysis, spam detection, and a short discussion regarding chatbots. The final chapter presents the Transformer architecture, BERT-based models, and the GPT family of models, all of which were developed during the past three years and considered SOTA ("state of the art"). The appendices contain introductory material (including Python code samples) on regular expressions and probability/statistical concepts. Companion files with source code and figures are included. FEATURES: Covers extensive topics related to natural language processing Includes separate appendices on regular expressions and probability/statistics Features companion files with source code and figures from the book.

As part of the best-selling Pocket Primer series, this book provides an overview of the major concepts to program using TensorFlow 2. The focus of this book is on basic programming instructions used in machine learning and deep learning. Includes companion files with source code (in Python) and figures. FEATURES: Provides an overview of the most important TensorFlow programming techniques used for machine learning, deep learning, linear and logical regression, etc. Covers TensorFlow 2 and previous versions that run with TF2. Includes companion files with source code (in Python) and figures.

This book is intended primarily for developers who have little or no experience with Python or Pandas. It contains a fast-paced introduction to Python and Python-based solutions to various tasks. Chapter 1 provides a quick tour of basic Python 3, followed by a chapter that shows how to work with loops and conditional logic in Python. Chapter 3 discusses data structures in Python, followed by a chapter that features code samples for tasks with strings and arrays in Python. Chapter 5 contains concepts in object-oriented programming, along with code samples that illustrate how they are implemented in Python. Chapter 6 introduces recursion and some fundamental topics in combinatorics. Finally, the appendix provides an introduction to Pandas. Companion files with code and figures are available for downloading from the publisher. Features: Provides the reader with basic Python 3 and Pandas programming concepts. Companion files with code and figures

As part of the best-selling Pocket Primer series, this book is primarily for data scientists and machine learning engineers who want to expand their current knowledge of SQL using MySQL as the primary RDBMS. It includes Python-based code samples to access data from a MySQL table in a Pandas data frame and Java-based code samples for accessing data in a MySQL database, along with XML documents and JSON documents. The book also introduces NoSQL, presents an overview of MongoDB, and SQLite--an open-source RDBMS availableon mobile devices. The final chapter of the book covers a diverse set of miscellaneous topics, such as normalization, schemas, database optimization, and performance. Numerous code samples and listings are included to support myriad topics. Companion files with source code and figures are available from the publisher. FEATURES: Covers extensive topics related to SQL, using MySQL as the primary RDBMS Introduces NoSQL, presents an overview of MongoDB, and SQLite--an open-source RDBMS available on mobile devices Features companion files with source code and figures from the book

This book provides readers with enough information for them to develop more sophisticated Angular applications that incorporate deep learning. The first three chapters of this book contain a short tour of basic Angular functionality, such as UI components and forms in Angular applications. The fourth chapter introduces you to deep learning, the problems it can solve, and some challenges for the future. You will also learn about MLPs (Multi Layer Perceptrons), CNNs (Convolutional Neural Networks), and a Keras-based code sample of a CNN with the MNIST dataset. The fifth chapter discusses RNNs (Recurrent Neural Networks), BPTT (Back Propagation Through Time), as well as LSTMs (Long Short Term Memory) and AEs (Auto Encoders). The sixth chapter introduces basic TensorFlow concepts, followedby tensorflowjs (i.e., TensorFlow in modern browsers), and some examples of Angular applications combined with deep learning.

As part of the best-selling Pocket Primer Series, this book is designed to introduce the reader to the basic concepts of data science using Python 3 and other computer applications. It is intended to be a fast-paced introduction to some basic features of data analytics and also covers statistics, data visualization, linear algebra, and regular expressions. The book includes numerous code samples using Python, NumPy, R, SQL, NoSQL, and Pandas. Companion files with source code and color figures are available. FEATURES: Includes a concise introduction to Python 3 and linear algebra Provides a thorough introduction to data visualization and regular expressions Covers NumPy, Pandas, R, and SQL Introduces probability and statistical concepts Features numerous code samples throughout Includes companion files with source code and figures

This book is designed to provide the reader with basic Python3 programming concepts related to machine learning. The first four chapters provide a fast-paced introduction to Python 3, NumPy, and Pandas. The fifth chapter introduces the fundamental concepts of machine learning. The sixth chapter is devoted to machine learning classifiers, such as logistic regression, k-NN, decision trees, random forests, and SVMs. The final chapter includes material on NLP and RL. Keras-based code samples are included to supplement the theoretical discussion. The book also contains separate appendices for regular expressions, Keras, and TensorFlow 2. Features: Provides the reader withbasic Python3 programming concepts related to machine learning Includes separate appendices for regular expressions, Keras, and TensorFlow 2

As part of the new Pocket Primer series, this book provides an overview of the major aspects and the source code to use Python 2. It covers the latest Python developments, built-in functions and custom classes, data visualization, graphics, databases, and more. It includes a companion disc with appendices, source code, and figures. This Pocket Primer is primarily for self-directed learners who want to learn Python 2 and it serves as a starting point for deeper exploration of Python programming. Features: Includes a companion disc with appendices, source code, and figures Contains material devoted to Raspberry Pi, Roomba, JSON, and Jython Includes latest Python 2 developments, built-in functions and custom classes, data visualization, graphics, databases, and more Provides a solid introduction to Python 2 via complete code samples On the CD-ROM: Appendices (HTML5 and JavaScript Toolkits, Jython, SPA) Source code samples All images from the text (including 4-color) Solutions to Odd-Numbered Exercises

This book begins with an introduction to AI, followed by machine learning, deep learning, NLP, and reinforcement learning. Readers will learn about machine learningclassifiers such as logistic regression, k-NN, decision trees, random forests,and SVMs. Next, the book covers deep learning architectures such as CNNs, RNNs,LSTMs, and auto encoders. Keras-based code samples are included to supplementthe theoretical discussion. In addition, this book contains appendices forKeras, TensorFlow 2, and Pandas.

As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to the basic concepts of data analytics using Python 3. It is intended to be a fast-paced introduction to some basic features of data analytics and also covers statistics, data visualization, and data cleaning. The book includes numerous code samples using NumPy, Pandas, Matplotlib, Seaborn, and features an appendix on regular expressions. Companion files with source code and color figures are available. FEATURES: Includes a concise introduction to Python 3. Provides a thorough introduction to data and data cleaning. Covers NumPy and Pandas. Introduces statistical concepts and data visualization (Matplotlib/Seaborn). Features an appendix on regular expressions. Includes companion files with source code and figures.

As part of the new Pocket Primer series, this book provides an overview of the major aspects, the source code, and tutorial videos to use jQuery. DVD with code, videos, and graphics included. Features: Integrated coverage of CSS3, jQuery and other important JS toolkits Covers jQuery Mobile and HTML5 hybrid mobile apps Covers BackboneJS and Twitter Bootstrap Includes companion DVD with source code, tutorial videos, and 4-color graphics

As part of the best-selling Pocket Primer series, this book is designed to prepare programmers for machine learning and deep learning/TensorFlow topics. It begins with a quick introduction to Python, followed by chapters that discuss NumPy, Pandas, Matplotlib, and scikit-learn. The final two chapters contain an assortment of TensorFlow 1.x code samples, including detailed code samples for TensorFlow Dataset (which is used heavily in TensorFlow 2 as well). A TensorFlow Dataset refers to the classes in the tf.data.Dataset namespace that enables programmers to construct a pipeline of data by means of method chaining so-called lazy operators, e.g., map(), filter(), batch(), and so forth, based on data from one or more data sources. Companion files with source code are available for downloading from the publisher. FEATURES, A practical introduction to Python, NumPy, Pandas, Matplotlib, and introductory aspects of TensorFlow 1.x, Contains relevant NumPy/Pandas code samples that are typical in machine learning topics, and also useful TensorFlow 1.x code samples for deep learning/TensorFlow topics, Includes many examples of TensorFlow Dataset APIs with lazy operators, e.g., map(), filter(), batch(), take() and also method chaining such operators, Assumes the reader has very limited experience, Includes companion files with all of the source code examples (download from the publisher).

As part of the Pocket Primer series, this book provides an overview of the major aspects and the source code to use D3. This Pocket Primer is primarily for self-directed learners who want to learn D3 and serves as a starting point for deeper exploration of its programming. Features: Includes a companion disc with appendices, source code, and figures Contains material devoted to D3 on mobile devices, using D3 with Ajax, HTML5 Web Sockets, NodeJS, and covers D3 application programming interfaces and other toolkits Provides a solid introduction to D3 via complete code samples eBook Customers: Companion files are available for downloading with order number/proof of purchase by writing to the publisher at [email protected].

As part of the new Pocket Primer series, this book provides an overview of the major aspects, the source code, and tutorial videos to use HTML5. DVD with code, videos, and graphics included. eBook Customers: Companion files are available for downloading with order number/proof of purchase by writing to the publisher at [email protected]. Table of Contents: 1. HTML5 Semantic Markup. 2. Introduction to CSS3. 3. SVG Essentials. 4. Introduction to HTML5 Canvas. 5. Media and Hardware Support HTML5. 6. Storage, Databases, GeoLocation, and Offline Apps. 7. Browser-Server Communication. 8. Miscellaneous HTML5 APIs. 9. HTML5 Mobile Apps on Android and iOS. 10. jQuery Concepts. Appendix A. jQuery Concepts (Part 2). Appendix B. Introduction to Android.

As part of the best selling Pocket Primer series, this book provides an overview of the major aspects and the source code to use the latest versions of Android. It has coverage of the fundamental aspects of Android that are illustrated via code samples for versions 4.x through 7.x and features the Google Pixel phone. This Pocket Primer is primarily for self-directed learners who want to learn Android programming and it serves as a starting point for deeper exploration of its numerous applications. Companion disc (also available for downloading from the publisher) with source code, images, and appendices. Features: Contains latest material on Android VR, graphics/animation, apps, and features the new Google Pixel phone Includes companion files with all of the source code, appendices, and images from the book Provides coverage of the fundamental aspects of Android that are illustrated via code samples for versions 4.x through 7.x On the Companion Files: Source code samples All images from the text (including 4-color) Appendices

As part of the best-selling Pocket Primer series, this book is designed to introduce beginners to TensorFlow 1.x fundamentals for basic machine learning algorithms in TensorFlow. It is intended to be a fast-paced introduction to various ""core""features of TensorFlow, with code samples that cover deep learning and TensorFlow basics. The material in the chapters illustrates how to solve a variety of tasks after which you can do further reading to deepen your knowledge. Companion files with all of the code samples are available for downloading from the publisher by writing to [email protected]. Features: Uses Python for code samples Covers TensorFlow APIs and Datasets Assumes the reader has very limited experience Companion files with all of the source code examples (download from the publisher)

Covers the features of HTML5, CSS3 graphics, jQuery, and jQuery Mobile, and also shows how you can extend the power of CSS3 with SVG. Designed for readers with some knowledge of CSS/HTML/JavaScript, but more advanced users will benefit from numerous graphics techniques that are illustrated in many code samples. DVD with code and graphics included. You'll see examples that help you learn to: create mobile Web applications using jQuery and jQuery Mobile; render HTML5/CSS3/SVG Web pages in Android and iOS; and create 2D/3D graphics & animation effects with CSS3. A companion DVD with source code and graphics is included. Features: Learn how to create Web Pages with jQuery and jQuery Mobile Create mobile apps in Android and iOS with HTML5/CSS3/SVG Create Web Pages with jQuery with CSS3 Learn about upcoming CSS3 features such as CSS3 Shaders and Regions Create 2D/3D graphics and animation effects with CSS3 Render 2D shapes, charts, and graphs with gradients in HTML5 Canvas Includes companion DVD with source code and 4-color graphics