Book Content
chapters • 15h44m total length
1. Developing building blocks for Deep RL using TensorFlow 2.x
2. Implementing value-based, policy gradients and actor-critic Deep RL algorithms
3. Implementing Advanced Deep RL algorithms
4. RL in real-world: Building intelligent trading agents
5. RL in Real-World: Building Stock Trading Agents
6. RL in real-world: Building intelligent agents to complete your ToDos
7. Deploying Deep RL Agents to the Cloud
8. Building cross-platform (web, desktop, mobile) Deep-RL Apps using TensorFlow 2.x
9. Distributed training and automated production deployment pipeline for Deep RL Apps
