The 3 fantastic technical books from my reading in 2019-2020:

  • Hands-on Machine Learning with Sci-kit and Tensorflow 2.0 - by Aurélien Géron
  • Hands-On Machine Learning with Scikit-Learn, Keras, and Tensorflow: Concepts, Tools, and Techniques to Build Intelligent Systems by Sebastian Raschka
  • Grokking Deep Learning by Andrew Trask

  1. Hands-on Machine Learning with Sci-kit and Tensorflow 2.0 - by Aurélien Géron Covers a lot of material and it took me a while to complete the book. It is hands down the best book to learn in this space. At the time I was reading the book all the solutions to the exercises were not available. Code at the author’s github repo.

  2. Hands-On Machine Learning with Scikit-Learn, Keras, and Tensorflow: Concepts, Tools, and Techniques to Build Intelligent Systems by Sebastian Raschka Another great book. Covers less material than the previous book but is very easy to follow and understand. No specific exercises at the end of the chapter. Code at the author’s github repo.

  3. Grokking Deep Learning by Andrew Trask The first few chapters are deceptively simple and the material becomes more challenging as one progresses through the book. The last few chapters are mostly on NLP. Code at the author’s github repo.

Other interesting books I read

  • The Visual Display of Quantitative Information by Edward Tufte
  • Storytelling with Data: A Data Visualization Guide for Business Professionals by Cole Nussbaumer Knaflic