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[FreeCourseSite.Com] Udemy - Artificial Intelligence Reinforcement Learning In Python

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[FreeCourseSite.com] Udemy - Artificial Intelligence Reinforcement Learning in Python

NAME: [FreeCourseSite.com] Udemy - Artificial Intelligence Reinforcement Learning in Python.torrent

CATEGORY: Other

INFOHASH: 2c2ece5a1762052507c7237eff15c94a55f65c72

SIZE: 1.2 GB in 99 files

ADDED: Uploaded on 09-01-2019 by our crawler pet called "Spidey".

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Description

Udemy - Artificial Intelligence Reinforcement Learning in Python

The complete guide to artificial intelligence and machine learning, prep for deep reinforcement learning.

Created by Lazy Programmer Inc.
Last updated 1/2019

For more Udemy Courses: https://freecoursesite.com

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Files in this torrent

FILENAME		SIZE
	1. Introduction and Outline/1. Introduction and outline.mp4	10.1 MB
	1. Introduction and Outline/1. Introduction and outline.vtt	12 KB
	1. Introduction and Outline/2. What is Reinforcement Learning.mp4	22 MB
	1. Introduction and Outline/2. What is Reinforcement Learning.vtt	24 KB
	1. Introduction and Outline/3. Where to get the Code.mp4	4.5 MB
	1. Introduction and Outline/3. Where to get the Code.vtt	4.9 KB
	1. Introduction and Outline/4. Strategy for Passing the Course.mp4	9.5 MB
	1. Introduction and Outline/4. Strategy for Passing the Course.vtt	10.7 KB
	2. Return of the Multi-Armed Bandit/1. Problem Setup and The Explore-Exploit Dilemma.mp4	6.5 MB
	2. Return of the Multi-Armed Bandit/1. Problem Setup and The Explore-Exploit Dilemma.vtt	7.1 KB
	2. Return of the Multi-Armed Bandit/2. Epsilon-Greedy.mp4	2.8 MB
	2. Return of the Multi-Armed Bandit/2. Epsilon-Greedy.vtt	2.9 KB
	2. Return of the Multi-Armed Bandit/3. Updating a Sample Mean.mp4	2.2 MB
	2. Return of the Multi-Armed Bandit/3. Updating a Sample Mean.vtt	2 KB
	2. Return of the Multi-Armed Bandit/4. Comparing Different Epsilons.mp4	8 MB
	2. Return of the Multi-Armed Bandit/4. Comparing Different Epsilons.vtt	4.9 KB
	2. Return of the Multi-Armed Bandit/5. Optimistic Initial Values.mp4	5.1 MB
	2. Return of the Multi-Armed Bandit/5. Optimistic Initial Values.vtt	3 KB
	2. Return of the Multi-Armed Bandit/6. UCB1.mp4	8.2 MB
	2. Return of the Multi-Armed Bandit/6. UCB1.vtt	7.4 KB
	2. Return of the Multi-Armed Bandit/7. Bayesian Thompson Sampling.mp4	51.8 MB
	2. Return of the Multi-Armed Bandit/7. Bayesian Thompson Sampling.vtt	11 KB
	2. Return of the Multi-Armed Bandit/8. Thompson Sampling vs. Epsilon-Greedy vs. Optimistic Initial Values vs. UCB1.mp4	10.6 MB
	2. Return of the Multi-Armed Bandit/8. Thompson Sampling vs. Epsilon-Greedy vs. Optimistic Initial Values vs. UCB1.vtt	5.5 KB
	2. Return of the Multi-Armed Bandit/9. Nonstationary Bandits.mp4	7.5 MB
	2. Return of the Multi-Armed Bandit/9. Nonstationary Bandits.vtt	7.1 KB
	3. Build an Intelligent Tic-Tac-Toe Agent/1. Naive Solution to Tic-Tac-Toe.mp4	6.1 MB
	3. Build an Intelligent Tic-Tac-Toe Agent/1. Naive Solution to Tic-Tac-Toe.vtt	6.6 KB
	3. Build an Intelligent Tic-Tac-Toe Agent/10. Tic Tac Toe Code Main Loop and Demo.mp4	9.4 MB
	3. Build an Intelligent Tic-Tac-Toe Agent/10. Tic Tac Toe Code Main Loop and Demo.vtt	8.4 KB
	3. Build an Intelligent Tic-Tac-Toe Agent/11. Tic Tac Toe Summary.mp4	8.3 MB
	3. Build an Intelligent Tic-Tac-Toe Agent/11. Tic Tac Toe Summary.vtt	9.3 KB
	3. Build an Intelligent Tic-Tac-Toe Agent/2. Components of a Reinforcement Learning System.mp4	12.7 MB
	3. Build an Intelligent Tic-Tac-Toe Agent/2. Components of a Reinforcement Learning System.vtt	13.4 KB
	3. Build an Intelligent Tic-Tac-Toe Agent/3. Notes on Assigning Rewards.mp4	4.2 MB
	3. Build an Intelligent Tic-Tac-Toe Agent/3. Notes on Assigning Rewards.vtt	4.5 KB
	3. Build an Intelligent Tic-Tac-Toe Agent/4. The Value Function and Your First Reinforcement Learning Algorithm.mp4	103.7 MB
	3. Build an Intelligent Tic-Tac-Toe Agent/4. The Value Function and Your First Reinforcement Learning Algorithm.vtt	21.7 KB
	3. Build an Intelligent Tic-Tac-Toe Agent/5. Tic Tac Toe Code Outline.mp4	5 MB
	3. Build an Intelligent Tic-Tac-Toe Agent/5. Tic Tac Toe Code Outline.vtt	5.9 KB
	3. Build an Intelligent Tic-Tac-Toe Agent/6. Tic Tac Toe Code Representing States.mp4	4.4 MB
	3. Build an Intelligent Tic-Tac-Toe Agent/6. Tic Tac Toe Code Representing States.vtt	4.5 KB
	3. Build an Intelligent Tic-Tac-Toe Agent/7. Tic Tac Toe Code Enumerating States Recursively.mp4	9.8 MB
	3. Build an Intelligent Tic-Tac-Toe Agent/7. Tic Tac Toe Code Enumerating States Recursively.vtt	10.3 KB
	3. Build an Intelligent Tic-Tac-Toe Agent/8. Tic Tac Toe Code The Environment.mp4	10 MB
	3. Build an Intelligent Tic-Tac-Toe Agent/8. Tic Tac Toe Code The Environment.vtt	10.9 KB
	3. Build an Intelligent Tic-Tac-Toe Agent/9. Tic Tac Toe Code The Agent.mp4	9 MB
	3. Build an Intelligent Tic-Tac-Toe Agent/9. Tic Tac Toe Code The Agent.vtt	10 KB
	4. Markov Decision Proccesses/1. Gridworld.mp4	3.4 MB
	4. Markov Decision Proccesses/1. Gridworld.vtt	3.7 KB
	4. Markov Decision Proccesses/2. The Markov Property.mp4	7.2 MB
	4. Markov Decision Proccesses/2. The Markov Property.vtt	7.7 KB
	4. Markov Decision Proccesses/3. Defining and Formalizing the MDP.mp4	6.6 MB
	4. Markov Decision Proccesses/3. Defining and Formalizing the MDP.vtt	7.2 KB
	4. Markov Decision Proccesses/4. Future Rewards.mp4	5.2 MB
	4. Markov Decision Proccesses/4. Future Rewards.vtt	5.5 KB
	4. Markov Decision Proccesses/5. Value Function Introduction.mp4	19.7 MB
	4. Markov Decision Proccesses/5. Value Function Introduction.vtt	14.5 KB
	4. Markov Decision Proccesses/6. Value Functions.mp4	8.3 MB
	4. Markov Decision Proccesses/6. Value Functions.vtt	11 KB
	4. Markov Decision Proccesses/7. Bellman Examples.mp4	87.1 MB
	4. Markov Decision Proccesses/7. Bellman Examples.vtt	25.8 KB
	4. Markov Decision Proccesses/8. Optimal Policy and Optimal Value Function.mp4	3.2 MB
	4. Markov Decision Proccesses/8. Optimal Policy and Optimal Value Function.vtt	4.7 KB
	4. Markov Decision Proccesses/9. MDP Summary.mp4	2.4 MB
	4. Markov Decision Proccesses/9. MDP Summary.vtt	2.4 KB
	5. Dynamic Programming/1. Intro to Dynamic Programming and Iterative Policy Evaluation.mp4	4.8 MB
	5. Dynamic Programming/1. Intro to Dynamic Programming and Iterative Policy Evaluation.vtt	4.9 KB
	5. Dynamic Programming/10. Dynamic Programming Summary.mp4	8.3 MB
	5. Dynamic Programming/10. Dynamic Programming Summary.vtt	8.6 KB
	5. Dynamic Programming/2. Gridworld in Code.mp4	11.5 MB
	5. Dynamic Programming/2. Gridworld in Code.vtt	10 KB
	5. Dynamic Programming/3. Iterative Policy Evaluation in Code.mp4	12.1 MB
	5. Dynamic Programming/3. Iterative Policy Evaluation in Code.vtt	9.3 KB
	5. Dynamic Programming/4. Policy Improvement.mp4	4.5 MB
	5. Dynamic Programming/4. Policy Improvement.vtt	4.7 KB
	5. Dynamic Programming/5. Policy Iteration.mp4	3.1 MB
	5. Dynamic Programming/5. Policy Iteration.vtt	3.2 KB
	5. Dynamic Programming/6. Policy Iteration in Code.mp4	7.6 MB
	5. Dynamic Programming/6. Policy Iteration in Code.vtt	5.6 KB
	5. Dynamic Programming/7. Policy Iteration in Windy Gridworld.mp4	9.1 MB
	5. Dynamic Programming/7. Policy Iteration in Windy Gridworld.vtt	7.5 KB
	5. Dynamic Programming/8. Value Iteration.mp4	6.2 MB
	5. Dynamic Programming/8. Value Iteration.vtt	6.4 KB
	5. Dynamic Programming/9. Value Iteration in Code.mp4	4.9 MB
	5. Dynamic Programming/9. Value Iteration in Code.vtt	3 KB
	6. Monte Carlo/1. Monte Carlo Intro.mp4	5 MB
	6. Monte Carlo/1. Monte Carlo Intro.vtt	5.4 KB
	6. Monte Carlo/2. Monte Carlo Policy Evaluation.mp4	8.8 MB
	6. Monte Carlo/2. Monte Carlo Policy Evaluation.vtt	9.8 KB
	6. Monte Carlo/3. Monte Carlo Policy Evaluation in Code.mp4	7.9 MB
	6. Monte Carlo/3. Monte Carlo Policy Evaluation in Code.vtt	5.6 KB
	6. Monte Carlo/4. Policy Evaluation in Windy Gridworld.mp4	7.8 MB
	6. Monte Carlo/4. Policy Evaluation in Windy Gridworld.vtt	4.9 KB
	6. Monte Carlo/5. Monte Carlo Control.mp4	9.3 MB
	6. Monte Carlo/5. Monte Carlo Control.vtt	9.3 KB
	6. Monte Carlo/6. Monte Carlo Control in Code.mp4	10.2 MB
	6. Monte Carlo/6. Monte Carlo Control in Code.vtt	5.3 KB
	6. Monte Carlo/7. Monte Carlo Control without Exploring Starts.mp4	4.6 MB

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[FreeCourseSite.Com] Udemy - Artificial Intelligence Reinforcement Learning In Python

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