With the subtitle "Developing Enterprise Applications in JavaScript" this book shows how to use Oracle's JavaScript Extension Toolkit (JET) for internal back office and intranet applications. Author Daniel Curtis walks through the process of developing a functional application using Oracle JET. The example built throughout the book is a support ticket system using a variety of different components bundled with the toolkit, including lists, inputs, and visualizations.

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Subtitled "Greedy Algorithms and Dynamic Programming", this book, based on Professor Tim Roughgarden's Stanford/Coursera MOOC, sets out to be an accessible, no-nonsense, and programming language-agnostic introduction to algorithms. The book includes hints or solutions to all quizzes and problems, and a series of YouTube videos accompanies the book. Part 3 covers greedy algorithms (scheduling, minimum spanning trees, clustering, Huffman codes) and dynamic programming (knapsack, sequence alignment, shortest paths, optimal search trees).

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Subtitled Theory and Practice for Next-Generation Spatial Computing, in this book, authors Erin Pangilinan, Steve Lukas, and Vasanth Mohan examine the AR and VR development pipeline and provide hands-on practice to help hone skills. Step-by-step tutorials show how to build practical applications and experiences grounded in theory. Industry specialists, including Timoni West, Victor Prisacariu, and Nicolas Meuleau, are used to help explain the technology behind spatial computing.

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This book shows how to use the Bash command-line shell interface to communicate with the operating system kernel and how to employ Bash's programming abilities. Author Mike McGrath begins by demonstrating Bash commands for system navigation and file manipulation, and moves on to describe advanced features such as command history, command-line editing, and environment customization. He introduces Bash programming with examples of flow control, command switches, input/output, and debugging so readers learn how to create their own executable programs by copying the examples.

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This is the second edition of a best selling Python book that gives a straightforward introduction to the core of Python programming. Author Eric Matthes provides a foundation in general programming concepts, Python fundamentals, and problem solving. Three real world projects in the second part of the book allow readers to apply their knowledge in useful ways by creating a simple video game, using data visualization techniques to make graphs and charts, and building and deploying an interactive web application.

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Subtitled "Computer Modeling & Animation", this book is a manual describing the operation of Blender version 2.80. In this revised 5th edition, author John M. Blain coversthe new improved interface, new workspaces and new eevee render system. The book also introduces the program's graphical user interface and shows how to implement tools for modeling and animating characters and creating scenes with the application of color, texture and special lighting effects.

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This book is written for the general reader with no previous programming experience with an entire chapter is dedicated to learning the basics of Python and R. Then, each chapter presents step-by-step instructions and walkthroughs for solving data science problems using Python and R. Authors Chantal  and Daniel Larose cover topics including data preparation, exploratory data analysis, preparing to model the data, decision trees, model evaluation, misclassification costs, naïve Bayes classification, neural networks, clustering, regression modeling, dimension reduction, and association rules mining.Topics such as random forests and general linear models are also included. 

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Based on discussions with practitioners and executives from more than a hundred organizations, ranging from data-driven companies such as Google, LinkedIn, and Facebook, to governments and traditional corporate enterprises, this book authored by Alex Gorelik presents a collection of essays. The book covers what a data lake is, why enterprises need one, data lake implementation, examining data lake initiatives, analytic projects, experiences, and best practices informed by data experts working in various industries.

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With the subtitle, Build Database Apps in Elixir for Scalability and Performance, this book shows how to use Ecto, the database library for Elixir, to connect Elixir and Phoenix apps to databases. Authors Darin Wilson and Eric Meadows-Jonsson begin from Ecto fundamentals with a module-by-module tour, then move on to more advanced topics and advice on best practices. They also provide a series of recipes featuring more advanced topics, such as changing your pooling strategy to maximize your database's efficiency, and using nested associations to handle complex table relationships.

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Subtitled "Artificial Intelligence Solutions Using Microsoft Cognitive Services and TensorFlow", this book aims to make deep learning and machine learning accessible to everyday developers, by providing a combination of tools such as cognitive services APIs, machine learning platforms, and libraries.Adnan Masood and Adnan Hashmi cover the business case for machine learning and deep learning, with coverage of topics such as digital assistants, computer vision, text analytics, speech, and robotics process automation. The book focuses on Microsoft Cognitive Services, with recipes using multiple environments including TensowFlow and CNTK.

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This hands-on guide shows how to build high-quality cross-platform mobile and web apps. Author Nader Dabit jumps right into building a complete app with the help of clear, easy-to-follow instructions before moving on to more-advanced topics like styling, APIs, animations, and data architecture. The book also shows how to maximize code reuse without sacrificing native platform look-and-feel. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats.

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This book provides a hands-on, readable guide to applying machine learning to real-world problems. Aimed at both experienced R users and developers new to the language, author Brett Lantz covers the topics needed to uncover key insights, make new predictions, and visualize data findings. This new 3rd edition updates the classic R data science book with newer and better libraries, advice on ethical and bias issues in machine learning, and an introduction to deep learning.

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