Book Content
chapters • 11h8m total length
1. Deep Learning –Architectures and Frameworks
2. Training Reinforcement Learning Agents Using OpenAI Gym
3. Markov Decision Process (MDP)
4. Policy Gradients
5. Q-Learning & Deep Q Networks
6. Asynchronous Methods
7. Robo Everything – Real Strategy Gaming
8. AlphaGo – Reinforcement learning at it’s Best
9. Reinforcement Learning in Autonomous Driving
10. Financial Portfolio Management
11. Reinforcement Learning in Robotics
12. Deep Reinforcement Learning in AdTech
13. Reinforcement Learning in Image Processing
14. Deep Reinforcement Learning in NLP
15. Appendix 1.Further topics in Reinforcement Learning
