Artificial Intelligence IV - Reinforcement Learning in Java (Udemy.com)
All you need to know about Markov Decision processes, value- and policy-iteation as well as about Q learning approach
Created by: Holczer Balazs
Produced in 2021
What you will learn
- Understand reinforcement learning
- Understand Markov Decision Processes
- Understand value- and policy-iteration
- Understand Q-learning approach and it's applications
Quality Score
Overall Score : 82 / 100
Course Description
- Markov Decision Processes
- value-iteration and policy-iteration
- Q-learning fundamentals
- pathfinding algorithms with Q-learning
- Q-learning with neural networks
- Anyone who wants to understand artificial intelligence and reinforcement learning!
Instructor Details
- 4.1 Rating
7 Reviews
Holczer Balazs
Hi!
My name is Balazs Holczer. I am from Budapest, Hungary. I am qualified as a physicist. At the moment I am working as a simulation engineer at a multinational company. I have been interested in algorithms and data structures and its implementations especially in Java since university. Later on I got acquainted with machine learning techniques, artificial intelligence, numerical methods and recipes such as solving differential equations, linear algebra, interpolation and extrapolation. These things may prove to be very very important in several fields: software engineering, research and development or investment banking. I have a special addiction to quantitative models such as the Black-Scholes model, or the Merton-model.
Take a look at my website if you are interested in these topics!
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