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Best Deep Learning Books You Must Read

Below I’ll give you my selections for the best Deep Learning books by a few categories. I will cover these and other great books more in depth later.

1. Deep Learning with Python (2017)

Best Deep Learning Books You Must ReadDeep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that…
Author(s): Francois Chollet

2. Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems (2017)

Best Deep Learning Books You Must Read.Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—scikit-learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques,…
Author(s): Aurélien Géron

3. The Hundred-Page Machine Learning Book (2019)

Best Deep Learning Books You Must Readto avoid counterfeit, make sure that the book . Avoid third-party sellers. , Research Director at Google, co-author of , the most popular AI textbook in the world: “Burkov has undertaken a very useful but impossibly hard task in reducing all of machine learning to 100 pages. He succeeds well in choosing the topics — both theory and practice — that will be useful to practitioners, and for the reader who understands that this is the first 100 (or actually 150) pages you will read, not the last, provides a solid introduction to the field.” ,…
Author(s): Andriy Burkov

4. Mastering Deep Learning Fundamentals with Python: The Absolute Ultimate Guide for Beginners To Expert and Step By Step Guide to Understand Python Programming Concepts (2019)

Best Deep Learning Books You Must Read★★Buy the Paperback Version of this Book and get the Kindle Book version for FREE ★★Step into the fascinating world of data science..You to participate in the revolution that brings artificial intelligence back to the heart of our society, thanks to data scientists.Data science consists in translating problems of any other nature into quantitative modeling problems, solved by processing algorithms.This book, designed for anyone wishing to learn Deep Learning. This book presents the main techniques: deep neural networks, able to model all kinds of data, convolution networks, able to…
Author(s): Richard Wilson

5. Grokking Deep Learning (2019)

Best Deep Learning Books You Must ReadGrokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. Deep learning, a branch of artificial intelligence, teaches computers to learn by using neural networks, technology inspired by the human brain. Online text translation, self-driving…
Author(s): Andrew Trask

6. Deep Learning (MIT Press Essential Knowledge series) (2019)

Best Deep Learning Books You Must ReadDeep learning is an artificial intelligence technology that enables computer vision, speech recognition in mobile phones, machine translation, AI games, driverless cars, and other applications. When we use consumer products from Google, Microsoft, Facebook, Apple, or Baidu, we are often interacting with a deep learning system. In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution.Kelleher explains that deep learning enables…
Author(s): John D. Kelleher

7. Deep Learning: A Practitioner’s Approach (2017)

Best Deep Learning Books You Must ReadAlthough interest in machine learning has reached a high point, lofty expectations often scuttle projects before they get very far. How can machine learning—especially deep neural networks—make a real difference in your organization? This hands-on guide not only provides the most practical information available on the subject, but also helps you get started building efficient deep learning networks.Authors Adam Gibson and Josh Patterson provide theory on deep learning before introducing their open-source Deeplearning4j (DL4J) library for developing production-class…
Author(s): Josh Patterson, Adam Gibson

8. Deep Learning and the Game of Go (2019)

Best Deep Learning Books You Must ReadDeep Learning and the Game of Go teaches you how to apply the power of deep learning to complex reasoning tasks by building a Go-playing AI. After exposing you to the foundations of machine and deep learning, you’ll use Python to build a bot and then teach it the rules of the game. Foreword by Thore Graepel, DeepMind Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. The ancient strategy game of Go is an incredible case study for AI. In 2016, a deep learning-based system shocked the Go world by defeating a…
Author(s): Max Pumperla, Kevin Ferguson

9. Deep Learning Cookbook: Practical Recipes to Get Started Quickly (2018)

Best Deep Learning Books You Must ReadDeep learning doesn’t have to be intimidating. Until recently, this machine-learning method required years of study, but with frameworks such as Keras and Tensorflow, software engineers without a background in machine learning can quickly enter the field. With the recipes in this cookbook, you’ll learn how to solve deep-learning problems for classifying and generating text, images, and music.Each chapter consists of several recipes needed to complete a single project, such as training a music recommending system. Author Douwe Osinga also provides a…
Author(s): Douwe Osinga

10. Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more (2018)

Best Deep Learning Books You Must ReadKey Features Book DescriptionRecent developments in reinforcement learning (RL), combined with deep learning (DL), have seen unprecedented progress made towards training agents to solve complex problems in a human-like way. Google’s use of algorithms to play and defeat the well-known Atari arcade games has propelled the field to prominence, and researchers are generating new ideas at a rapid pace.Deep Reinforcement Learning Hands-On is a comprehensive guide to the very latest DL tools and their limitations. You will evaluate methods including…
Author(s): Maxim Lapan

11. Deep Learning with R (2018)

Best Deep Learning Books You Must ReadDeep Learning with R introduces the world of deep learning using the powerful Keras library and its R language interface. The book builds your understanding of deep learning through intuitive explanations and practical examples. Continue your journey into the world of deep learning with Deep Learning with R in Motion, a practical, hands-on video course available exclusively at Manning.com (www.manning.com/livevideo/deep-​learning-with-r-in-motion). Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. Machine learning has made remarkable progress in…
Author(s): Francois Chollet, J. J. Allaire

12. Artificial Intelligence Engines: A Tutorial Introduction to the Mathematics of Deep Learning (2019)

Best Deep Learning Books You Must Read“authoritative, funny, and concise”Steven Strogatz, Professor of Applied Mathematics, Cornell University.The brain has always had a fundamental advantage over conventional computers: it can learn. However, a new generation of artificial intelligence algorithms, in the form of deep neural networks, is rapidly eliminating that advantage. Deep neural networks rely on adaptive algorithms to master a wide variety of tasks, including cancer diagnosis, object recognition, speech recognition, robotic control, chess, poker, backgammon and Go, at super-human levels of performance. In this richly illustrated book, key neural network learning algorithms…
Author(s): James V Stone

13. Hands-On Unsupervised Learning Using Python: How to Build Applied Machine Learning Solutions from Unlabeled Data (2019)

Best Deep Learning Books You Must ReadMany industry experts consider unsupervised learning the next frontier in artificial intelligence, one that may hold the key to the holy grail in AI research, the so-called general artificial intelligence. Since the majority of the world's data is unlabeled, conventional supervised learning cannot be applied; this is where unsupervised learning comes in. Unsupervised learning can be applied to unlabeled datasets to discover meaningful patterns buried deep in the data, patterns that may be near impossible for humans to uncover.Author Ankur Patel provides practical knowledge on how to apply unsupervised learning using two…
Author(s): Ankur A. Patel

Categories: Machine Learning, Reinforcement Learning, Deep Learning, Deep Reinforcement Learning, Artificial Intelligence. If the Deep Learning book is considered the Bible for Deep Learning, this masterpiece earns that title for Reinforcement Learning. If you want to get started in RL, this is the way. Just like you predicted (pat on the back And even other deep learning books straddle the line, giving you a healthy dose of theory while enabling you to “get your hands dirty” and learn by implementing (these tend to be my favorite deep learning books). For each deep learning book I’ll discuss the core concepts covered, the target audience, and if the book is appropriate for you. Neural networks and deep learning currently provide the best solutions to many problems in image recognition, speech recognition, and natural language processing. This book will teach you many of the core concepts behind neural networks and deep learning. For more details about the approach taken in the book, see here. MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville. If this repository helps you in anyway, show your love ️ by putting a ⭐️ on this project ️ Deep Learning. An MIT Press book Ian Goodfellow and Yoshua Bengio and Aaron Courville The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular. The online version of the book is now complete and will remain available online for free. The deep learning textbook can now be ordered on Amazon.

We highly recommend you to buy all paper or e-books in a legal way, for example, on Amazon. But sometimes it might be a need to dig deeper beyond the shiny book cover. Before making a purchase, you can visit resources like Genesis and download some deep learning books mentioned below at your own risk. Once again, we do not host any illegal or copyrighted files, but simply give our visitors a choice and hope they will make a wise decision.

Advances in Deep Learning

Author(s): M. Arif Wani, Farooq Ahmad Bhat, Saduf Afzal, Asif Iqbal Khan
Publisher: Springer, Year: 2020, Size: 7 Mb, Download: pdf
ID: 2348685

Deep Learning Classifiers with Memristive Networks: Theory and Applications

Author(s): Alex Pappachen James
Publisher: Springer International Publishing, Year: 2020, Size: 9 Mb, Download: pdf
ID: 2407612

Recent Advances in Big Data and Deep Learning: Proceedings of the INNS Big Data and Deep Learning Conference INNSBDDL2019, held at Sestri Levante, Genova, Italy 16-18 April 2019

Author(s): Luca Oneto, Nicolò Navarin, Alessandro Sperduti, Davide Anguita
Publisher: Springer International Publishing, Year: 2020, Size: 22 Mb, Download: pdf
ID: 2408021

Big Data Analysis and Deep Learning Applications

Author(s): Thi Thi Zin, Jerry Chun-Wei Lin
Publisher: Springer Singapore, Year: 2019, Size: 55 Mb, Download: pdf
ID: 2254749

Learn Keras for Deep Neural Networks: A Fast-Track Approach to Modern Deep Learning with Python

Author(s): Jojo John Moolayil
Publisher: Apress, Year: 2019, Size: 3 Mb, Download: pdf
ID: 2295774

Practical Computer Vision Applications Using Deep Learning with CNNs: With Detailed Examples in Python Using TensorFlow and Kivy

Author(s): Ahmed Fawzy Gad
Publisher: Apress, Year: 2019, Size: 10 Mb, Download: pdf
ID: 2295779

Deep Learning and Missing Data in Engineering Systems

Author(s): Collins Achepsah Leke, Tshilidzi Marwala
Publisher: Springer International Publishing, Year: 2019, Size: 6 Mb, Download: pdf
ID: 2309686

Linking and Mining Heterogeneous and Multi-view Data

Author(s): Deepak P, Anna Jurek-Loughrey
Publisher: Springer International Publishing, Year: 2019, Size: 7 Mb, Download: pdf
ID: 2309839

Embedded Deep Learning: Algorithms, Architectures and Circuits for Always-on Neural Network Processing

Author(s): Bert Moons, Daniel Bankman, Marian Verhelst
Publisher: Springer International Publishing, Year: 2019, Size: 8 Mb, Download: pdf
ID: 2312216

Python Deep Learning: Exploring deep learning techniques, neural network architectures and GANs with PyTorch, Keras and TensorFlow

Author(s): Ivan Vasilev, Daniel Slater, Gianmario Spacagna, Peter Roelants, Valentino Zocca
Publisher: Packt Publishing, Year: 2019, Size: 24 Mb, Download: pdf
ID: 2319010

Please note that this booklist is not definite. Some books are really hot items according to Washington Post, others are written by unknown authors. On top of that, you can always find additional tutorials and courses on Coursera, Udemy or edX, for example. Are there any other relevant links you could recommend? Leave a comment if you have any feedback on the list.

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