PyTorch 1.x Reinforcement Learning Cookbook. Over 60 recipes to design, develop, and deploy self-learning AI models using Python

Yuxi (Hayden) Liu

Reinforcement learning (RL) is a branch of machine learning that has gained popularity in recent times. It allows you to train AI models that learn from their own actions and optimize their behavior. PyTorch has also emerged as the preferred tool for training RL models because of its efficiency and ease of use.With this book, you'll explore the important RL concepts and the implementation of algorithms in PyTorch 1.x. The recipes in the book, along with real-world examples, will help you master various RL techniques, such as dynamic programming, Monte Carlo simulations, temporal difference, and Q-learning. You'll also gain insights into industry-specific applications of these techniques. Later chapters will guide you through solving problems such as the multi-armed bandit problem and the cartpole problem using the multi-armed bandit algorithm and function approximation. You'll also learn how to use Deep Q-Networks to complete Atari games, along with how to effectively implement policy gradients. Finally, you'll discover how RL techniques are applied to Blackjack, Gridworld environments, internet advertising, and the Flappy Bird game.By the end of this book, you'll have developed the skills you need to implement popular RL algorithms and use RL techniques to solve real-world problems.

Data Ingestion with Python Cookbook. A practical guide to ingesting, monitoring, and identifying errors in the data ingestion process

Gláucia Esppenchutz

Data Ingestion with Python Cookbook offers a practical approach to designing and implementing data ingestion pipelines. It presents real-world examples with the most widely recognized open source tools on the market to answer commonly asked questions and overcome challenges.You’ll be introduced to designing and working with or without data schemas, as well as creating monitored pipelines with Airflow and data observability principles, all while following industry best practices. The book also addresses challenges associated with reading different data sources and data formats. As you progress through the book, you’ll gain a broader understanding of error logging best practices, troubleshooting techniques, data orchestration, monitoring, and storing logs for further consultation.By the end of the book, you’ll have a fully automated set that enables you to start ingesting and monitoring your data pipeline effortlessly, facilitating seamless integration with subsequent stages of the ETL process.

iOS 14 Programming for Beginners. Get started with building iOS apps with Swift 5.3 and Xcode 12 - Fifth Edition

Ahmad Sahar

If you're looking to work and experiment with powerful iOS 14 features such as widgets and App Clips to create your own apps, this iOS programming guide is for you. The book offers a comprehensive introduction for experienced programmers who are new to iOS, taking you through the entire process of learning the Swift language, writing your own apps, and publishing them on the App Store.Fully updated to cover the new iOS 14 features, along with Xcode 12 and Swift 5.3, this fifth edition of iOS 14 Programming for Beginners starts with an introduction to the Swift programming language and shows you how to accomplish common programming tasks with it. You'll then start building the user interface (UI) of a complete real-world app using the storyboards feature in the latest version of Xcode and implement the code for views, view controllers, data managers, and other aspects of mobile apps. The book will also help you apply iOS 14 features to existing apps and introduce you to SwiftUI, a new way to build apps for all Apple devices. Finally, you’ll set up testers for your app and understand what you need to do to publish your app on the App Store.By the end of this book, you'll not only be well versed in writing and publishing applications, but you’ll also be able to apply your iOS development skills to enhance existing apps.

Adobe Animate 2022 for Creative Professionals. Implement professional techniques and create vivid animated and interactive content with Animate - Second Edition

Joseph Labrecque

Adobe Animate is platform-agnostic asset creation, motion design, animation, and interactivity software. Complete with explanations of essential concepts and step-by-step walkthroughs of practical examples, this book will guide you in using Adobe Animate to create immersive experiences by breaking through creative limitations across every medium.We begin by getting up to speed with all that you need to know about Adobe Animate. You'll learn how to get started with Animate as a creative platform and explore the features introduced in its most recent versions. The book will show you how to consume and produce media assets for multiple platforms through both the publish and export workflows. Following this, you’ll explore advanced rigging techniques and discover how to create more dynamic animation with advanced depth and movement techniques. You’ll also find out how to build projects such as games, virtual reality experiences, and apps for various platforms as the book demonstrates different ways to use Animate. Finally, it covers the different methods used to extend the software for various needs.By the end of this Adobe Animate book, you'll be able to produce a variety of media assets, motion graphic design materials, animated artifacts, and interactive content pieces for platforms such as HTML5 Canvas, WebGL, and mobile devices.

Building Data-Driven Applications with Danfo.js. A practical guide to data analysis and machine learning using JavaScript

Rising Odegua, Stephen Oni

Most data analysts use Python and pandas for data processing for the convenience and performance these libraries provide. However, JavaScript developers have always wanted to use machine learning in the browser as well. This book focuses on how Danfo.js brings data processing, analysis, and ML tools to JavaScript developers and how to make the most of this library to build data-driven applications.Starting with an overview of modern JavaScript, you’ll cover data analysis and transformation with Danfo.js and Dnotebook. The book then shows you how to load different datasets, combine and analyze them by performing operations such as handling missing values and string manipulations. You’ll also get to grips with data plotting, visualization, aggregation, and group operations by combining Danfo.js with Plotly. As you advance, you’ll create a no-code data analysis and handling system and create-react-app, react-table, react-chart, Draggable.js, and tailwindcss, and understand how to use TensorFlow.js and Danfo.js to build a recommendation system. Finally, you’ll build a Twitter analytics dashboard powered by Danfo.js, Next.js, node-nlp, and Twit.js.By the end of this app development book, you’ll be able to build and embed data analytics, visualization, and ML capabilities into any JavaScript app in server-side Node.js or the browser.

Mastering Hadoop. Go beyond the basics and master the next generation of Hadoop data processing platforms

Sandeep Karanth

WebRTC Integrator's Guide. Successfully build your very own scalable WebRTC infrastructure quickly and efficiently

Altanai Bisht

Python Data Analysis Cookbook. Clean, scrape, analyze, and visualize data with the power of Python!

Ivan Idris

Data analysis is a rapidly evolving field and Python is a multi-paradigm programming language suitable for object-oriented application development and functional design patterns. As Python offers a range of tools and libraries for all purposes, it has slowly evolved as the primary language for data science, including topics on: data analysis, visualization, and machine learning.Python Data Analysis Cookbook focuses on reproducibility and creating production-ready systems. You will start with recipes that set the foundation for data analysis with libraries such as matplotlib, NumPy, and pandas. You will learn to create visualizations by choosing color maps and palettes then dive into statistical data analysis using distribution algorithms and correlations. You’ll then help you find your way around different data and numerical problems, get to grips with Spark and HDFS, and then set up migration scripts for web mining.In this book, you will dive deeper into recipes on spectral analysis, smoothing, and bootstrapping methods. Moving on, you will learn to rank stocks and check market efficiency, then work with metrics and clusters. You will achieve parallelism to improve system performance by using multiple threads and speeding up your code.By the end of the book, you will be capable of handling various data analysis techniques in Python and devising solutions for problem scenarios.