{"product_id":"the-reinforcement-learning-workshop-learn-how-to-apply-cutting-edge-reinforcement-learning-algorithms-to-a-wide-range-of-control-problems-paperback","title":"The Reinforcement Learning Workshop: Learn how to apply cutting-edge reinforcement learning algorithms to a wide range of control problems - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eAlessandro Palmas\u003c\/b\u003e (Author), \u003cb\u003eEmanuele Ghelfi\u003c\/b\u003e (Author), \u003cb\u003eAlexandra Galina Petre\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eStart with the basics of reinforcement learning and explore deep learning concepts such as deep Q-learning, deep recurrent Q-networks, and policy-based methods with this practical guide\u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eKey Features\u003c\/strong\u003e\u003c\/p\u003e \u003cul\u003e \u003cli\u003eUse TensorFlow to write reinforcement learning agents for performing challenging tasks\u003c\/li\u003e \u003cli\u003eLearn how to solve finite Markov decision problems\u003c\/li\u003e \u003cli\u003eTrain models to understand popular video games like Breakout\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003cstrong\u003eBook Description\u003c\/strong\u003e\u003c\/p\u003e \u003cp\u003eVarious intelligent applications such as video games, inventory management software, warehouse robots, and translation tools use reinforcement learning (RL) to make decisions and perform actions that maximize the probability of the desired outcome. This book will help you to get to grips with the techniques and the algorithms for implementing RL in your machine learning models.\u003c\/p\u003e \u003cp\u003eStarting with an introduction to RL, you'll be guided through different RL environments and frameworks. You'll learn how to implement your own custom environments and use OpenAI baselines to run RL algorithms. Once you've explored classic RL techniques such as Dynamic Programming, Monte Carlo, and TD Learning, you'll understand when to apply the different deep learning methods in RL and advance to deep Q-learning. The book will even help you understand the different stages of machine-based problem-solving by using DARQN on a popular video game Breakout. Finally, you'll find out when to use a policy-based method to tackle an RL problem.\u003c\/p\u003e \u003cp\u003eBy the end of The Reinforcement Learning Workshop, you'll be equipped with the knowledge and skills needed to solve challenging problems using reinforcement learning.\u003c\/p\u003e \u003cp\u003e\u003cstrong\u003eWhat you will learn\u003c\/strong\u003e\u003c\/p\u003e \u003cul\u003e \u003cli\u003eUse OpenAI Gym as a framework to implement RL environments\u003c\/li\u003e \u003cli\u003eFind out how to define and implement reward function\u003c\/li\u003e \u003cli\u003eExplore Markov chain, Markov decision process, and the Bellman equation\u003c\/li\u003e \u003cli\u003eDistinguish between Dynamic Programming, Monte Carlo, and Temporal Difference Learning\u003c\/li\u003e \u003cli\u003eUnderstand the multi-armed bandit problem and explore various strategies to solve it\u003c\/li\u003e \u003cli\u003eBuild a deep Q model network for playing the video game Breakout\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003cstrong\u003eWho this book is for\u003c\/strong\u003e\u003c\/p\u003e \u003cp\u003eIf you are a data scientist, machine learning enthusiast, or a Python developer who wants to learn basic to advanced deep reinforcement learning algorithms, this workshop is for you. A basic understanding of the Python language is necessary.\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 822\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 1.63 x 9.25 x 7.5 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e August 14, 2020\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":47440143614173,"sku":"9781800200456","price":79.29,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0811\/9867\/8237\/files\/YUXQkSRRyA9781800200456.webp?v=1771435858","url":"https:\/\/handfulofbooks.com\/products\/the-reinforcement-learning-workshop-learn-how-to-apply-cutting-edge-reinforcement-learning-algorithms-to-a-wide-range-of-control-problems-paperback","provider":"Handful of Books","version":"1.0","type":"link"}