Udemy - Reinforcement Learning Essentials and Classical Methods

  • Category Other
  • Type Tutorials
  • Language English
  • Total size 3.5 GB
  • Uploaded By freecoursewb
  • Downloads 190
  • Last checked 4 days ago
  • Date uploaded 4 months ago
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Infohash : AEB90D80B07DF7F6E53669F1D1A41F8C97180636



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

Files:

[ WebToolTip.com ] Udemy - Reinforcement Learning Essentials and Classical Methods
  • Get Bonus Downloads Here.url (0.2 KB)
  • ~Get Your Files Here ! 1 - Introduction
    • 1 -Introduction.mp4 (51.3 MB)
    • 2 -What's Reinforcement Learning.mp4 (29.1 MB)
    • 3 -Components of Reinforcement Learning.mp4 (18.2 MB)
    2 - Python Programming (Optional)
    • 1 -What is Python.mp4 (45.4 MB)
    • 10 -Dictionaries and Advanced Data Structures.mp4 (142.6 MB)
    • 11 -Modules, Packages & Importing Libraries.mp4 (137.7 MB)
    • 12 -File Handling.mp4 (89.0 MB)
    • 13 -Exception Handling & Robust Code.mp4 (139.4 MB)
    • 14 -OOP.mp4 (137.7 MB)
    • 15 -Advanced List Operations & Comprehensions.mp4 (94.2 MB)
    • 16 -Visualization Basics.mp4 (148.3 MB)
    • 2 -Anaconda & Jupyter & Visual Studio Code.mp4 (31.7 MB)
    • 3 -Google Colab.mp4 (45.1 MB)
    • 4 -Environment Setup.mp4 (43.6 MB)
    • 5 -Python Syntax & Basic Operations.mp4 (258.7 MB)
    • 6 -Data Structures Lists, Tuples, Sets.mp4 (155.4 MB)
    • 7 -Control Structures & Looping.mp4 (111.6 MB)
    • 8 -Functions & Basic Functional Programming.mp4 (143.0 MB)
    • 9 -Intermediate Functions.mp4 (86.5 MB)
    3 - Mathematical Foundations
    • 1 -Thompson Sampling.mp4 (102.4 MB)
    • 10 -Dynamic Programming - Python Code.mp4 (50.7 MB)
    • 11 -Dynamic Programming - Python Code Output.mp4 (5.6 MB)
    • 12 -Policy Evaluation.mp4 (147.5 MB)
    • 13 -Iterative Policy Evaluation Algorithm with Python.mp4 (62.5 MB)
    • 2 -Upper Confidence Bound (UCB) in Reinforcement Learning.mp4 (65.8 MB)
    • 3 -Markov Decision Processes.mp4 (36.4 MB)
    • 4 -Markov Decision Processes - Case.mp4 (16.5 MB)
    • 5 -Markov Decision Processes - Python.mp4 (28.9 MB)
    • 6 -Markov Decision Processes Code Output.mp4 (11.8 MB)
    • 7 -Dynamic Programming Principles.mp4 (16.1 MB)
    • 8 -Dynamic Programming - Case.mp4 (6.6 MB)
    • 9 -Dynamic Programming - Mathematical Model.mp4 (14.9 MB)
    4 - Monte Carlo Methods
    • 1 -Monte Carlo Methods in RL.mp4 (49.1 MB)
    • 2 -Blackjack - Intro.mp4 (33.4 MB)
    • 3 -Blackjack Python.mp4 (157.8 MB)
    • 4 -Blackjack Output.mp4 (15.5 MB)
    5 - Temporal Difference Learning
    • 1 -What is SARSA.mp4 (71.3 MB)
    • 2 -SARSA - Taxi Implementation.mp4 (153.1 MB)
    • 4 -Q-Learning Intro.mp4 (60.2 MB)
    • 5 -Frozen Lake.mp4 (107.7 MB)
    • 6 -Frozen Lake Python.mp4 (237.0 MB)
    • 7 -Cliff Walking Python.mp4 (216.6 MB)
    • Bonus Resources.txt (0.1 KB)

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