Neural Networks and Deep Learning by Michael Nielsen.Interpretable Machine Learning by Christoph Molnar.An Introduction to Machine Learning Interpretability (2nd Edition) by Patrick Hall & Navdeep Gill.Machine Learning Yearning by Andrew Ng.Rebooting AI by Gary Marcus & Ernest Davis.The Book of Why by Judea Pearl, Dana Mackenzie.Abu-Mostafa, Malik Magdon-Ismail, Hsuan-Tien Lin. TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers by Pete Warden & Daniel Situnayake.Deep Reinforcement Learning Hands-On (2nd Edition) by Maxim Lapan.Reinforcement Learning: An Introduction (2nd Edition) by Richard S.Deep Learning by Ian Goodfellow, Yoshua Bengio, Aaron Courville.Deep Learning with Python by Francois Chollet.Building Machine Learning Powered Applications: Going from Idea to Product by Emmanuel Ameisen.
The Hundred-Page Machine Learning Book by Andriy Burkov.Hands-On Machine Learning with Scikit-Learn and TensorFlow (2nd Edition) by Aurélien Géron.Here it is - the list of the best machine learning & deep learning books for 2020: I did my fair share of digging to pull together this list so you don't have to. New year, new books! As I did last year, I've come up with the best recently-published titles on deep learning and machine learning.
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