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.
- Deep Learning with Python (2017)
- Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems (2017)
- The Hundred-Page Machine Learning Book (2019)
- 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)
- Grokking Deep Learning (2019)
- Deep Learning (MIT Press Essential Knowledge series) (2019)
- Deep Learning: A Practitioner’s Approach (2017)
- Deep Learning and the Game of Go (2019)
- Deep Learning Cookbook: Practical Recipes to Get Started Quickly (2018)
- Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more (2018)
- Deep Learning with R (2018)
- Artificial Intelligence Engines: A Tutorial Introduction to the Mathematics of Deep Learning (2019)
- Hands-On Unsupervised Learning Using Python: How to Build Applied Machine Learning Solutions from Unlabeled Data (2019)
Deep Learning with Python (2017)
Deep 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.
Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems (2017)
.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.
The Hundred-Page Machine Learning Book (2019)
to 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.
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)
★★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 quantita…
Grokking Deep Learning (2019)
Grokking 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.
Although 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?
Deep 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.
Deep 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.
Deep Reinforcement Learning Hands-On: Apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more (2018)
Key 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.
Deep Learning with R (2018)
Deep 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.
“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.
Hands-On Unsupervised Learning Using Python: How to Build Applied Machine Learning Solutions from Unlabeled Data (2019)
Many 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.
Best Deep Learning Books You Must Read
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 Library 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.
Deep Learning Pipeline: Building A Deep Learning Model With TensorFlow
Author(s): Hisham El-Amir, Mahmoud Hamdy
ID: 2452069, Publisher: 2020, Year: Apress, Size: 12 Mb, Format: pdf
Deep Learning With Pytorch. Code
Author(s): Eli Stevens, Luca Antiga, Thomas Viehmann
ID: 2551178, Publisher: Manning Pubns Co, Year: 2021, Size: 169 Mb, Format: zip
Handbook of Deep Learning in Biomedical Engineering: Techniques and Applications
Author(s): Valentina Emilia Balas, Brojo Kishore Mishra, Raghvendra Kumar
ID: 2831815, Publisher: , Year: 2021, Size: 14 Mb, Format: pdf
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.