Description
Advanced Reinforcement Learning in Python: cutting-edge DQNs is an advanced reinforcement learning course in Python published by Udemy Academy. During this training course, you will get to know the process of developing and building artificial intelligence-based assistants that use different deep learning and reinforcement learning techniques. There are various algorithms in the field of deep reinforcement learning. During this training course, you will learn about the implementation process of the most advanced and important algorithms with the PyTorch framework and the PyTorch lightning tool. Implementing a set of adaptive algorithms that are able to solve a set of controlled tasks with a specific technical structure based on their previous experiences is one of the most important skills taught in this course.
In the final part of this training course, you will combine all the skills learned and the taught materials together and use them in the development of an assistant based on artificial intelligence. This assistant is fully adaptive and can make decisions in different situations and act based on the decisions made using artificial neural networks and many deep learning methods defined for it.
What you will learn in the Advanced Reinforcement Learning in Python: cutting-edge DQNs course:
- Advanced reinforcement learning
- PyTorch framework
- Hyperparameter tuning with Optuna
- Reinforcement learning with raw image data
- Advanced and applied reinforcement learning algorithms
- Building artificial intelligence with the ability to make decisions in different situations
- Getting to know the learning process for each of the algorithms
- Debugging and developing the operating range of different algorithms
- And …
Course details
Publisher: Yudmi
teacher: Escape Velocity Labs
English language
Training level: introductory to advanced
Number of courses: 102
Training duration: 8 hours and 26 minutes
Course headings
Advanced Reinforcement Learning in Python course prerequisites: cutting-edge DQNs
Be comfortable programming in Python
Completing our course “Reinforcement Learning beginner to master” or being familiar with the basics of Reinforcement Learning (or watching the leveling sections included in this course).
Know basic statistics (mean, variance, normal distribution)
Course images
Advanced Reinforcement Learning in Python: cutting-edge DQNs introduction video
Installation guide
After Extract, view with your favorite Player.
English subtitle
Quality: 720p
download link
Password file(s): www.downloadly.ir
Size
2.4 GB
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