Here it is — the list of the best machine learning & deep learning books for 2019.
- Deep Learning by Ian Goodfellow, Yoshua Bengio, Aaron Courville
- Grokking Deep Learning by Andrew W. Trask
- Deep Learning with Python by Francois Chollet
- Hands-On Machine Learning with Scikit-Learn and TensorFlow by Aurélien Géron
- The Hundred-Page Machine Learning Book by Andriy Burkov
- Reinforcement Learning: An Introduction (2nd Edition) by Richard S. Sutton, Andrew G. Barto
- Deep Reinforcement Learning Hands-On by Maxim Lapan
- Learning From Data by Yaser S. Abu-Mostafa, Malik Magdon-Ismail, Hsuan-Tien Lin.
- The Book of Why by Judea Pearl, Dana Mackenzie.
- Machine Learning Yearning by Andrew Ng.
- Interpretable Machine Learning by Christoph Molnar.
- Neural Networks and Deep Learning by Michael Nielsen.
No comments:
Post a Comment