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Reinforcement learning with TensorFlow and TRFL

Author: Jim DiLorenzo
Publisher: [Place of publication not identified] : Packt, [2019]
Edition/Format:   eVideo : Clipart/images/graphics : English
Summary:
"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  Read more...
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Material Type: Clipart/images/graphics, Internet resource, Videorecording
Document Type: Internet Resource, Computer File, Visual material
All Authors / Contributors: Jim DiLorenzo
OCLC Number: 1102269510
Notes: Title from title screen (viewed May 22, 2019).
Date of publication from resource description page.
Performer(s): Presenter, Jim DiLorenzo.
Description: 1 online resource (1 streaming video file (1 hr., 19 min., 1 sec.)) : digital, sound, color
Responsibility: Jim DiLorenzo.

Abstract:

"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."--Resource description page.

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