Explore this recipe-based guide to developing AI applications to solve a variety of real-world and business problems using reinforcement learning Key Features * Develop and deploy deep reinforcement learning-based solutions to production pipelines, products, and services * Explore popular reinforcement learning algorithms such as Q-learning, SARSA, and the actor-critic method * Customize and build RL-based applications for real-world tasks Book Description Deep reinforcement learning enables the building of intelligent agents, products, and services that can go beyond computer vision or perception to perform actions. TensorFlow 2.x is the latest major release of the most popular deep learning framework that is used to develop and train deep neural networks (DNNs). The book begins with an introduction to the fundamentals of deep reinforcement learning and the latest major version of TensorFlow 2.x. You'll then cover OpenAI Gym, model-based RL, and model-free RL, and learn how to develop basic agents. Moving on, you will discover how to implement advanced deep reinforcement learning algorithms such as actor-critic, deep deterministic policy gradients, deep-Q networks, proximal policy optimization, and deep recurrent Q-networks for training your RL agents. You'll also explore reinforcement learning in the real world by building cryptocurrency trading agents, stock/share trading agents, and intelligent agents for automating task completion. Lastly, you will find out how to deploy deep reinforcement learning agents to the cloud and build cross-platform apps using TensorFlow 2.x. By the end of this TensorFlow book, you will have gained a solid understanding of deep reinforcement learning algorithms with the help of easy-to-follow and concise implementations from scratch. What you will learn * Build deep reinforcement learning agents from scratch using the all-new TensorFlow 2.x and Keras API * Implement state-of-the-art deep reinforcement learning algorithms using minimal code * Train deep RL agents in simulated environments to perform real-world tasks such as cryptocurrency, stock trading, and building energy optimization * Deploy RL agents to the cloud and edge for real-world testing by creating desktop apps, cloud services, and web and mobile apps using TensorFlow 2.x * Speed up agent development using distributed DNN model training Who This Book Is For The book is for machine learning application developers, AI and applied AI researchers, data scientists, deep learning practitioners, and students with a basic understanding of the reinforcement learning concepts who want to build, train, and deploy their own reinforcement learning systems from scratch using TensorFlow 2.x.

Book Information
ISBN 9781838982546
Author Praveen Palanisamy
Format Paperback
Page Count 436
Imprint Packt Publishing Limited
Publisher Packt Publishing Limited
Weight(grams) 191g