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

Torrent Hash:
2C2ECE5A1762052507C7237EFF15C94A55F65C72
Number of Files:
165
Content Size:
1.19GB
Convert On:
2019-07-16
Keywords:
FreeCourseSitecomUdemyArtificialIntelligenceReinforcementLearninginPython
Magnet Link:
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File Name
Size
1. Introduction and Outline/1. Introduction and outline.mp4
10.1MB
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1. Introduction and Outline/1. Introduction and outline.vtt
12KB
1. Introduction and Outline/2. What is Reinforcement Learning.mp4
21.95MB
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1. Introduction and Outline/2. What is Reinforcement Learning.vtt
23.95KB
1. Introduction and Outline/3. Where to get the Code.mp4
4.46MB
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1. Introduction and Outline/3. Where to get the Code.vtt
4.92KB
1. Introduction and Outline/4. Strategy for Passing the Course.mp4
9.48MB
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1. Introduction and Outline/4. Strategy for Passing the Course.vtt
10.66KB
2. Return of the Multi-Armed Bandit/1. Problem Setup and The Explore-Exploit Dilemma.mp4
6.48MB
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2. Return of the Multi-Armed Bandit/1. Problem Setup and The Explore-Exploit Dilemma.vtt
7.12KB
2. Return of the Multi-Armed Bandit/2. Epsilon-Greedy.mp4
2.79MB
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2. Return of the Multi-Armed Bandit/2. Epsilon-Greedy.vtt
2.94KB
2. Return of the Multi-Armed Bandit/3. Updating a Sample Mean.mp4
2.17MB
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2. Return of the Multi-Armed Bandit/3. Updating a Sample Mean.vtt
2KB
2. Return of the Multi-Armed Bandit/4. Comparing Different Epsilons.mp4
8.02MB
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2. Return of the Multi-Armed Bandit/4. Comparing Different Epsilons.vtt
4.86KB
2. Return of the Multi-Armed Bandit/5. Optimistic Initial Values.mp4
5.13MB
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2. Return of the Multi-Armed Bandit/5. Optimistic Initial Values.vtt
3.04KB
2. Return of the Multi-Armed Bandit/6. UCB1.mp4
8.23MB
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2. Return of the Multi-Armed Bandit/6. UCB1.vtt
7.37KB
2. Return of the Multi-Armed Bandit/7. Bayesian Thompson Sampling.mp4
51.85MB
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2. Return of the Multi-Armed Bandit/7. Bayesian Thompson Sampling.vtt
11.04KB
2. Return of the Multi-Armed Bandit/8. Thompson Sampling vs. Epsilon-Greedy vs. Optimistic Initial Values vs. UCB1.mp4
10.57MB
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2. Return of the Multi-Armed Bandit/8. Thompson Sampling vs. Epsilon-Greedy vs. Optimistic Initial Values vs. UCB1.vtt
5.53KB
2. Return of the Multi-Armed Bandit/9. Nonstationary Bandits.mp4
7.49MB
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2. Return of the Multi-Armed Bandit/9. Nonstationary Bandits.vtt
7.09KB
3. Build an Intelligent Tic-Tac-Toe Agent/1. Naive Solution to Tic-Tac-Toe.mp4
6.11MB
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3. Build an Intelligent Tic-Tac-Toe Agent/1. Naive Solution to Tic-Tac-Toe.vtt
6.58KB
3. Build an Intelligent Tic-Tac-Toe Agent/10. Tic Tac Toe Code Main Loop and Demo.mp4
9.44MB
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3. Build an Intelligent Tic-Tac-Toe Agent/10. Tic Tac Toe Code Main Loop and Demo.vtt
8.39KB
3. Build an Intelligent Tic-Tac-Toe Agent/11. Tic Tac Toe Summary.mp4
8.32MB
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3. Build an Intelligent Tic-Tac-Toe Agent/11. Tic Tac Toe Summary.vtt
9.33KB
3. Build an Intelligent Tic-Tac-Toe Agent/2. Components of a Reinforcement Learning System.mp4
12.72MB
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3. Build an Intelligent Tic-Tac-Toe Agent/2. Components of a Reinforcement Learning System.vtt
13.4KB
3. Build an Intelligent Tic-Tac-Toe Agent/3. Notes on Assigning Rewards.mp4
4.23MB
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3. Build an Intelligent Tic-Tac-Toe Agent/3. Notes on Assigning Rewards.vtt
4.51KB
3. Build an Intelligent Tic-Tac-Toe Agent/4. The Value Function and Your First Reinforcement Learning Algorithm.mp4
103.72MB
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3. Build an Intelligent Tic-Tac-Toe Agent/4. The Value Function and Your First Reinforcement Learning Algorithm.vtt
21.69KB
3. Build an Intelligent Tic-Tac-Toe Agent/5. Tic Tac Toe Code Outline.mp4
5.04MB
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3. Build an Intelligent Tic-Tac-Toe Agent/5. Tic Tac Toe Code Outline.vtt
5.87KB
3. Build an Intelligent Tic-Tac-Toe Agent/6. Tic Tac Toe Code Representing States.mp4
4.42MB
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3. Build an Intelligent Tic-Tac-Toe Agent/6. Tic Tac Toe Code Representing States.vtt
4.5KB
3. Build an Intelligent Tic-Tac-Toe Agent/7. Tic Tac Toe Code Enumerating States Recursively.mp4
9.79MB
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3. Build an Intelligent Tic-Tac-Toe Agent/7. Tic Tac Toe Code Enumerating States Recursively.vtt
10.3KB
3. Build an Intelligent Tic-Tac-Toe Agent/8. Tic Tac Toe Code The Environment.mp4
10.05MB
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3. Build an Intelligent Tic-Tac-Toe Agent/8. Tic Tac Toe Code The Environment.vtt
10.88KB
3. Build an Intelligent Tic-Tac-Toe Agent/9. Tic Tac Toe Code The Agent.mp4
9.01MB
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3. Build an Intelligent Tic-Tac-Toe Agent/9. Tic Tac Toe Code The Agent.vtt
9.96KB
4. Markov Decision Proccesses/1. Gridworld.mp4
3.36MB
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4. Markov Decision Proccesses/1. Gridworld.vtt
3.69KB
4. Markov Decision Proccesses/2. The Markov Property.mp4
7.18MB
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4. Markov Decision Proccesses/2. The Markov Property.vtt
7.66KB
4. Markov Decision Proccesses/3. Defining and Formalizing the MDP.mp4
6.64MB
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4. Markov Decision Proccesses/3. Defining and Formalizing the MDP.vtt
7.16KB
4. Markov Decision Proccesses/4. Future Rewards.mp4
5.17MB
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4. Markov Decision Proccesses/4. Future Rewards.vtt
5.47KB
4. Markov Decision Proccesses/5. Value Function Introduction.mp4
19.72MB
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4. Markov Decision Proccesses/5. Value Function Introduction.vtt
14.5KB
4. Markov Decision Proccesses/6. Value Functions.mp4
8.28MB
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4. Markov Decision Proccesses/6. Value Functions.vtt
11.03KB
4. Markov Decision Proccesses/7. Bellman Examples.mp4
87.12MB
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25.79KB
4. Markov Decision Proccesses/8. Optimal Policy and Optimal Value Function.mp4
3.24MB
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4.69KB
4. Markov Decision Proccesses/9. MDP Summary.mp4
2.42MB
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4. Markov Decision Proccesses/9. MDP Summary.vtt
2.45KB
5. Dynamic Programming/1. Intro to Dynamic Programming and Iterative Policy Evaluation.mp4
4.83MB
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5. Dynamic Programming/1. Intro to Dynamic Programming and Iterative Policy Evaluation.vtt
4.91KB
5. Dynamic Programming/10. Dynamic Programming Summary.mp4
8.32MB
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11.46MB
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9.96KB
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12.07MB
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9.32KB
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4.54MB
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4.7KB
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3.17KB
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5.56KB
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9.1MB
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7.49KB
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6.19MB
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6.36KB
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4.9MB
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3.04KB
6. Monte Carlo/1. Monte Carlo Intro.mp4
4.98MB
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5.44KB
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8.76MB
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9.83KB
6. Monte Carlo/3. Monte Carlo Policy Evaluation in Code.mp4
7.92MB
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5.57KB
6. Monte Carlo/4. Policy Evaluation in Windy Gridworld.mp4
7.81MB
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4.85KB
6. Monte Carlo/5. Monte Carlo Control.mp4
9.26MB
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9.34KB
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10.17MB
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6. Monte Carlo/6. Monte Carlo Control in Code.vtt
5.33KB
6. Monte Carlo/7. Monte Carlo Control without Exploring Starts.mp4
4.63MB
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5.04KB
6. Monte Carlo/8. Monte Carlo Control without Exploring Starts in Code.mp4
8.06MB
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3.32KB
6. Monte Carlo/9. Monte Carlo Summary.mp4
5.71MB
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6. Monte Carlo/9. Monte Carlo Summary.vtt
6.47KB
7. Temporal Difference Learning/1. Temporal Difference Intro.mp4
2.72MB
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3.05KB
7. Temporal Difference Learning/2. TD(0) Prediction.mp4
5.82MB
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5.84KB
7. Temporal Difference Learning/3. TD(0) Prediction in Code.mp4
5.32MB
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3.62KB
7. Temporal Difference Learning/4. SARSA.mp4
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8.85KB
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5.05KB
7. Temporal Difference Learning/6. Q Learning.mp4
4.85MB
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5.37KB
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5.42MB
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7. Temporal Difference Learning/7. Q Learning in Code.vtt
3.14KB
7. Temporal Difference Learning/8. TD Summary.mp4
3.94MB
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4.27KB
8. Approximation Methods/1. Approximation Intro.mp4
6.46MB
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8. Approximation Methods/1. Approximation Intro.vtt
6.47MB
8. Approximation Methods/2. Linear Models for Reinforcement Learning.mp4
6.47MB
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6.76KB
8. Approximation Methods/3. Features.mp4
6.25MB
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8. Approximation Methods/3. Features.vtt
6.34KB
8. Approximation Methods/4. Monte Carlo Prediction with Approximation.mp4
2.85MB
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2.19KB
8. Approximation Methods/5. Monte Carlo Prediction with Approximation in Code.mp4
6.57MB
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8. Approximation Methods/5. Monte Carlo Prediction with Approximation in Code.vtt
3.67KB
8. Approximation Methods/6. TD(0) Semi-Gradient Prediction.mp4
8.35MB
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5.82KB
8. Approximation Methods/7. Semi-Gradient SARSA.mp4
4.7MB
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4.98KB
8. Approximation Methods/8. Semi-Gradient SARSA in Code.mp4
10.61MB
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4.93KB
8. Approximation Methods/9. Course Summary and Next Steps.mp4
13.24MB
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8. Approximation Methods/9. Course Summary and Next Steps.vtt
14.48KB
9. Appendix/1. What is the Appendix.mp4
5.45MB
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9. Appendix/1. What is the Appendix.vtt
3.38KB
9. Appendix/10. What order should I take your courses in (part 1).mp4
29.32MB
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9. Appendix/10. What order should I take your courses in (part 1).vtt
15.16KB
9. Appendix/11. What order should I take your courses in (part 2).mp4
37.62MB
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9. Appendix/11. What order should I take your courses in (part 2).vtt
22.3KB
9. Appendix/12. Where to get discount coupons and FREE deep learning material.mp4
4.03MB
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9. Appendix/12. Where to get discount coupons and FREE deep learning material.vtt
3.3KB
9. Appendix/2. Windows-Focused Environment Setup 2018.mp4
186.38MB
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9. Appendix/2. Windows-Focused Environment Setup 2018.vtt
18.94KB
9. Appendix/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4
43.92MB
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9. Appendix/3. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt
16.58KB
9. Appendix/4. How to Code by Yourself (part 1).mp4
24.53MB
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9. Appendix/4. How to Code by Yourself (part 1).vtt
27.34KB
9. Appendix/5. How to Code by Yourself (part 2).mp4
14.81MB
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9. Appendix/5. How to Code by Yourself (part 2).vtt
16.66KB
9. Appendix/6. How to Succeed in this Course (Long Version).mp4
18.31MB
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9. Appendix/6. How to Succeed in this Course (Long Version).vtt
13.71KB
9. Appendix/7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4
38.95MB
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9. Appendix/7. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt
29.9KB
9. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.mp4
78.33MB
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9. Appendix/8. Proof that using Jupyter Notebook is the same as not using it.vtt
13.18KB
9. Appendix/9. Python 2 vs Python 3.mp4
7.83MB
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9. Appendix/9. Python 2 vs Python 3.vtt
5.9KB
[CourseClub.NET].url
123B
[FCS Forum].url
133B
[FreeCourseSite.com].url
127B

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