Download Deep Learning and the Game of Go

Download Deep Learning and the Game of Go

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Deep Learning and the Game of Go

Download Deep Learning and the Game of Go

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Über den Autor und weitere Mitwirkende

Max Pumperla is a Data Scientist and Engineer specializing in Deep Learning at the artificial intelligence company skymind.ai. He is the co-founder of the Deep Learning platform aetros.com.Kevin Ferguson has 18 years of experience in distributed systems and data science. He is a data scientist at Honor, and has experience at companies such as Google and Meebo.

Produktinformation

Taschenbuch: 384 Seiten

Verlag: Manning Publications (6. Juni 2019)

Sprache: Englisch

ISBN-10: 1617295329

ISBN-13: 978-1617295324

Größe und/oder Gewicht:

18,4 x 1,9 x 22,9 cm

Durchschnittliche Kundenbewertung:

5.0 von 5 Sternen

3 Kundenrezensionen

Amazon Bestseller-Rang:

Nr. 30.370 in Fremdsprachige Bücher (Siehe Top 100 in Fremdsprachige Bücher)

A great book to look into machine learning - especially reinforcement learning. Max Pumperla did a great job teaching the reader on this important topic by guiding the reader to build an own Go Game Bot. Working on an interesting case makes the learning so much more fun!!! Thank you Max.If you google Max Pumperla you notice quickly that he is quite an expert in the field of machine learning and reinforcement learning. In his book he breaks the topic down so one can easily follow. But one notice quickly: he knows what he is talking about.FYI: Only a limited amount of Python is needed to have all the fun of learning more about the hot topic reinforcement learning. I use to code a little bit with basic python (numpy, pandas, basic stuff) and could follow the coding easily.If you only want to learn about reinforcement learning or about AlphaGo the book is also a great read (but this is not the focus).

One of the best strategies to master a discipline, is to pick one of the land-mark achievements, take it apart, and try to understand every bit of it.This is the approach taken here for the field of Deep-Learning.One of the recent break-through in Machine Learning was Google Deep-Mind creating a game engine Alpha-Go, that convincingly defeated even the strongest human Go players.Experts believed that results like these were probably 10 years in the future, if not more.The authors of the book walk you through, each of the step of the creation of the Alpha-Go engine.By the end of the book, you will have built a fully functional Deep-Learning Go engine, using state-of-the art Deep-Learning frameworks (Python/Keras) that is conceptually very similar to Alpha-Go and could (given enough training) beat human Go players as well.If you really want to understand how Deep Learning is working, this is an excellent starting point.Note that this is not a book about Go.What's particularly exciting about the presented approach is, that the method is very universal.Games like Chess, Connect-Four or Tic-Tac-Toe can be treated in complete analogy.Also real world applications, for example in robotics, can be approached with similar methods (Reinforcement Learning).Audience:This text is aimed at practitioners/developers that want to gain a thorough understanding of Deep-Learning.It is suitable for relative beginners, but also experts will find many interesting bits about Game-AIs and Reinforcement Learning, that make it a worthwhile read.Structure/Content:The book follows a concise path heading towards the goal of explaining the Alpha-Go engine.It covers background topics like Neural Networks, Go Engines, Python Libraries in separate chapters, that can be skipped.It is rather self-contained but does not try to fill pages with standard material.Difficulty:Demanding. Expect to sit down and work through code examples.

With a lot of machine learning / deep learning literature produced at the moment, it is always hard to decide on the best investment for your money. Deep Learning and the Game of Go sticks out with its hands-on approach to actually apply your learnings while reading the book.Progressing through the chapters, you'll not only learn the theories of deep and reinforcement learning but also actively implement a Go bot and improve it over time.Applying reinforcement learning to a game with exact rules is also a good approach for teaching this topic and it serves as a good building block in your Machine Learning career. From here, the reader can advance to more vague applications by herself, be it in finance, medicine, or other fields in the industry.

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Deep Learning and the Game of Go PDF

Deep Learning and the Game of Go PDF