There are a lot of great resources out there so I thought I would try to compile some of my favorites. This list contains books on deep learning, machine learning, and computer vision. These textbooks are all made freely available by the publisher.
Deep Learning
-
Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann (2020) - Official textbook from the PyTorch team.
-
Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville (2015) - The most popular textbook in deep learning. Free in HTML form. There’s not a PDF that you can simply download.
-
Neural Networks and Deep Learning by Michael Nielsen (2015) - This is no PDF of this one either. However, the layout on the website is beautiful and there are JavaScript elements in the text, so it wouldn’t work as well in PDF form anyway.
-
Dive into Deep Learning by Aston Zhang, Zack C. Lipton, Mu Li,and Alex J. Smola (2020)
-
First Contact With Deep Learning: Practical Introduction With Keras by Jordi Torres (2018)
General Machine Learning
-
Machine Learning Yearning by Andrew Ng (2018) - this is more about the machine learning process and how to build projects. It’s a short read. You have to provide an email address to download it. And while you’re there I would recommend leaving the checkbox for signing up to receive his newsletter, The Batch, checked as well because it’s a very good resource.
-
Interpretable Machine Learning: A Guide for Making Black Box Models Explainable by Christoph Molnar (2020)
Computer Vision
- Computer Vision: Algorithms and Applications by Richard Szeliski (2010) - The latest edition was published in 2010, so it predates the deep learning revolution.
- Update: The author is currently working on an update and has posted a draft with new material to the website. The new material includes deep learning as a separate chapter as well as incorporating it into other chapters.