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Advanced Reinforcement Learning in Python: cutting-edge DQNs is an advanced reinforcement learning course in Python published by Udemy Academy. During this training course, he will get acquainted with the process of developing and making assistants based on artificial intelligence, which are used using different breeding and strengthening techniques. Algorithms in the field of emotional enhancement are introduced during this training course with the development process of its most advanced and most important algorithms with PyTorch framework and 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, all the skills learned and taught materials are combined and used 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 several methods defined for it.
What you will learn in Advanced Reinforcement Learning in Python: cutting-edge DQNs
- 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 …
Instructors: Escape Velocity Labs
Level: Introductory to Advanced
Number of Lessons: 102
Duration: 8 hours and 26 minutes
Advanced Reinforcement Learning in Python: cutting-edge DQNs Prerequisites
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)
Advanced Reinforcement Learning in Python: cutting-edge DQNs introduction video
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