Description
The list of the best machine learning & deep learning books for 2020.
Summary
- New year, new books!
- This book offers a practical approach to RL by balancing theory with coding practice.
- With six new chapters devoted to a variety of up-to-the-minute developments in RL, including discrete optimization (solving the Rubik's Cube), multi-agent methods, Microsoft's TextWorld environment, advanced exploration techniques, and more, you will come away from this book with a deep understanding of the latest innovations in this emerging field.
- And you will have a foundation to use neural networks and deep learning to attack problems of your own devising Generative Deep Learning Teaching Machines to Paint, Write, Compose, and Play Last year was the year of Generative models, so you’ve probably heard about Generative Adversarial Networks.