Reinforcement Learning: With Open AI, TensorFlow and Keras Using Python by Abhis

Description: Reinforcement Learning by Abhishek Nandy, Manisha Biswas Estimated delivery 3-12 business days Format Paperback Condition Brand New Description Master reinforcement learning, a popular area of machine learning, starting with the basics: discover how agents and the environment evolve and then gain a clear picture of how they are inter-related. Youll then work with theories related to reinforcement learning and see the concepts that build up the reinforcement learning process. Reinforcement Learning discusses algorithm implementations important for reinforcement learning, including Markovs Decision process and Semi Markov Decision process. The next section shows you how to get started with Open AI before looking at Open AI Gym. Youll then learn about Swarm Intelligence with Python in terms of reinforcement learning. The last part of the book starts with the TensorFlow environment and gives an outline of how reinforcement learning can be applied to TensorFlow. Theres also coverage of Keras, a framework that can be used with reinforcement learning. Finally, youll delve into Googles Deep Mind and see scenarios where reinforcement learning can be used. What Youll Learn Absorb the core concepts of the reinforcement learning processUse advanced topics of deep learning and AIWork with Open AI Gym, Open AI, and Python Harness reinforcement learning with TensorFlow and Keras using PythonWho This Book Is ForData scientists, machine learning and deep learning professionals, developers who want to adapt and learn reinforcement learning. Author Biography Abhishek Nandy is B.Tech in IT and he is a constant learner.He is Microsoft MVP at Windows Platform,Intel Black belt Developer as well as Intel Software Innovator he has keen interest on AI,IoT and Game Development. Currently serving as a Application Architect in an IT Firm as well as consulting AI,IoT as well doing projects on AI,ML and Deep learning.He also is an AI trainer and driving the technical part of Intel AI Student developer program.He was involved in the first Make in India initiative where he was among top 50 innovators and got trained in IIMA.Manisha Biswas is BTech in Information Technology and currently working as a Software Developer at Insync Tech-Fin Solutions Ltd,in kolkata, India. Im involved with several areas of technology including Web Development, IoT,Soft Computing and Artificial Intelligence. I am an Intel Software Innovator and I was also awarded the SHRI DEWANG MEHTA IT AWARDS 2016 by NASSCOM,a certificate of excellence for top academic scores. I have very recently formed a WOMEN IN TECHNOLOGY Community at KoIKata,India to empower women to learn and explore new technologies.I always like to invent things,create something new,or to invent a new look for the old things. When not in front of my terminal, I am an explorer, a foodie, a doodler and a dreamer. I am always very passionate to share my knowledge and ideas with others. I am following the passion and doing the same currently by sharing my experiences to the community so that others can learn and also give shape to my ideas in a new way this lead me to become Google Women Techmakers Kolkata Chapter Lead. Details ISBN 1484232844 ISBN-13 9781484232842 Title Reinforcement Learning Author Abhishek Nandy, Manisha Biswas Format Paperback Year 2017 Pages 167 Edition 1st Publisher APress GE_Item_ID:137660622; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit. For purchases where a shipping charge was paid, there will be no refund of the original shipping charge. Additional Questions If you have any questions please feel free to Contact Us. Categories Baby Books Electronics Fashion Games Health & Beauty Home, Garden & Pets Movies Music Sports & Outdoors Toys

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