Write Reinforcement Learning agents in TensorFlow & TRFL, with ease
About This Video
The TRFL library is a collection of key algorithmic components that are used for a large number of DeepMind agents such as DQN, DDPG, and the Importance of Weighted Actor Learner Architecture. With this course, you will learn to implement classical RL algorithms as well as other cutting-edge techniques.
This course will help you get up-to-speed with the TRFL library quickly, so you can start building your own RL agents. Without wasting much time on theory, the course dives straightaway into designing and implementing RL algorithms.
By the end, you will be quite familiar with the tool and will be ready to put your knowledge into practice in your own projects.
The code bundle for this course is available at - https://github.com/PacktPublishing/Hands-On-Reinforcement-Learning-with-TensorFlow-TRFL
Downloading the example code for this course: You can download the example code files for all Packt video courses you have purchased from your account at http://www.PacktPub.com. If you purchased this course elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.