Python Reinforcement Learning Deep Qlearning And Trfl

Leverage the power of Reinforcement Learning techniques to develop intelligent systems using Python

Complete hands-on deep learning tutorial with Python. Learn Machine Learning, Matplotlib, Seaborn, Geoplotlib | Python

This book reviews research developments in diverse areas of reinforcement learning such as model-free actor-critic methods, model-based learning and control, information geometry of policy searches, reward design, and exploration in biology and the behavioral sciences. Special emphasis is placed on advanced ideas, algorithms, methods, and applications.

This book presents and develops new reinforcement learning methods that enable fast and robust learning on robots in real-time.

Statistical Methods for Dynamic Treatment Regimes shares state of the art of statistical methods developed to address questions of estimation and inference for dynamic treatment regimes, a branch of personalized medicine.

Reinforcement Learning: Deep Q-Learning, SARSA, Deep RL, with Car Racing and Trading Project and Project and Interview

Build Artificial Intelligence (AI) agents using Deep Reinforcement Learning and PyTorch: A2C, REINFORCE, DQN, etc.

Applied machine learning with a solid foundation in theory. Revised and expanded with TensorFlow 2, GANs, and reinforcement learning.