Cutting-Edge AI: Deep Reinforcement Learning in Python is part 11 of my deep learning series . The maturation of deep learning has propelled advances in reinforcement learning, which has been around since the 1980s . It’s only been recently that Deep Learning has really taken off, and along with it, Reinforcing Learning has also taken off . This is my 3rd reinforcement learning course, and this is the combination of two topics: Reinforcement and Deep Learning (Neural Networks) This is the first time I’ve taught Python Python has taught Python how to use the A2C algorithm, and the second time I’ve taught Python .
What you’ll learn in Cutting-Edge AI: Deep Support Knowing in Python
- Understand an innovative implementation of the A2C algorithm (OpenAI Baselines)
- Understand and execute Evolution Strategies (ES) for AI
- Understand and execute DDPG (Deep Deterministic Plan Slope)
Description
Welcome to Cutting-Edge AI!
This is technically Deep Learning in Python component 11 of my deep knowing series, as well as my third reinforcement discovering program.
Deep Reinforcement Understanding is actually the combination of 2 topics: Support Learning and also Deep Discovering (Neural Networks).
While both of these have been around for fairly a long time, it’s just been recently that Deep Discovering has truly removed, and also together with it, Reinforcement Understanding.
The maturation of deep discovering has moved breakthroughs in support discovering, which has been around because the 1980s, although some aspects of it, such as the Bellman equation, have been for much longer.
Who this course is for:
- Students and professionals who want to apply Reinforcement Learning to their work and projects
- Anyone who wants to learn cutting-edge Artificial Intelligence and Reinforcement Learning algorithms
File Name : | Cutting-Edge AI: Deep Reinforcement Learning in Python free download |
Content Source: | udemy |
Genre / Category: | Data Science |
File Size : | 1.77 gb |
Publisher : | Lazy Programmer Inc. |
Updated and Published: | 07 Jul,2022 |