What you'll learn
Understand reinforcement learning
Understand Markov Decision Processes
Understand value- and policy-iteration
Understand Q-learning approach and it's applications
Requirements
Basics AI knowledge: neural networks in the main
Description
This course is about Reinforcement Learning. The first step is to talk about the mathematical background: we can use a Markov Decision Process as a model for reinforcement learning. We can solve the problem 3 ways: value-iteration, policy-iteration and Q-learning. Q-learning is a model free approach so it is state-of-the-art approach. It learns the optimal policy by interacting with the environment. So these are the topics
Markov Decision Processes value-iteration and policy-iterationQ-learning fundamentalspathfinding algorithms with Q-learningQ-learning with neural networks
Who this course is for
Anyone who wants to understand artificial intelligence and reinforcement learning!


Download link

rapidgator.net:

Código:

https://rapidgator.net/file/6ea39c3c383ce4038fa30336b3b1081f/lkkou.Artificial.Intelligence.Iv..Reinforcement.Learning.In.Java.rar.html

nitroflare.com:

Código:

https://nitroflare.com/view/789CAB70B3816A2/lkkou.Artificial.Intelligence.Iv..Reinforcement.Learning.In.Java.rar

ddownload.com:

Código:

https://ddownload.com/aovul0xhokfa/lkkou.Artificial.Intelligence.Iv..Reinforcement.Learning.In.Java.rar

1dl.net:

Código:

https://1dl.net/eunizgxdvll6/lkkou.Artificial.Intelligence.Iv..Reinforcement.Learning.In.Java.rar