Reinforcement Learning Essentials and Classical Methods
https://WebToolTip.com
Published 8/2025
Created by Advancedor Academy
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English | Duration: 43 Lectures ( 9h 11m ) | Size: 3.5 GB
Learn the foundations of reinforcement learning through MDPs, dynamic programming, and Python examples.
What you'll learn
Understand the key components of reinforcement learning, including agents, environments, states, actions, rewards, and policies
Gain a clear understanding of Markov Decision Processes (MDPs) and how they form the foundation of RL problems
Apply dynamic programming techniques such as policy evaluation and value iteration using Python Explore model-free methods like Monte Carlo, SARSA, Q-Learning
See how RL problems are implemented and solved using environments like Blackjack, Taxi, Frozen Lake, and Cliff Walking
Requirements
No previous experience in machine learning or reinforcement learning is needed
A willingness to follow the logic behind RL step by step is more important than memorizing equations