... Book Description. The Deep Reinforcement Learning with Python, Second Edition book has several new chapters dedicated to new RL techniques, including distributional RL, imitation learning, inverse RL, and meta RL. How to code using Reinforcement Learning algorithms using TensorFlow and Python are explained very well in the book. Get started with a FREE account. The book starts with an introduction to Reinforcement Learning followed by OpenAI Gym, and TensorFlow. This book is all about reinforcement learning. Sign In. *FREE* shipping on qualifying offers. About the book. AI Crash Course: A fun and hands-on introduction to machine learning, reinforcement learning, deep learning, and artificial intelligence with Python [Ponteves, Hadelin de] on Amazon.com. Delve into the world of reinforcement learning algorithms and apply them to different use-cases via Python. Reinforcement Learning Algorithms with Python: Learn, understand, and develop smart algorithms for addressing AI challenges by Andrea Lonza. The book starts with an introduction to Reinforcement Learning followed by OpenAI and Tensorflow. Personalized experience. The book will also make you well skilled in formulating algorithms and techniques for your own applications. Reinforcement Learning: An Introduction R. S. Sutton and A. G. Barto. The intent of the book is to give you the best possible understanding of this field with a hands-on approach. Delve into the world of reinforcement learning algorithms and apply them to different use-cases via Python. Faster previews. The First Reinforcement Learning Tutorial Book with TensorFlow 2 Implementation. All Books. You will learn to leverage stable baselines, an improvement of OpenAI’s baseline library, to effortlessly implement popular RL algorithms. Reinforcement Learning with Python will help you to master basic reinforcement learning algorithms to the advanced deep reinforcement learning algorithms. In the first chapters, you'll start by learning the most fundamental concepts of reinforcement learning. You’ll also find this reinforcement learning book useful if you want to learn about the advancements in the field. Working knowledge of Python is necessary. Hands-On Reinforcement learning with Python will help you master not only the basic reinforcement learning algorithms but also the advanced deep reinforcement learning algorithms. AI Crash Course: A fun and hands-on introduction to machine learning, reinforcement learning, deep learning With significant enhancement in the quality and quantity of algorithms in recent years, this second edition of Hands-On Reinforcement Learning with Python has been completely revamped into an example-rich guide to learning state-of-the-art reinforcement learning (RL) and deep RL algorithms with TensorFlow and the OpenAI Gym toolkit. This book covers important topics such as policy gradients and Q learning, and utilizes frameworks such as Tensorflow, Keras, and OpenAI Gym. With the following software and hardware list you can run all code files present in the book (Chapter 1-11). This is a tutorial book on reinforcement learning, with explanation of theory and Python implementation. 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