Udemy - Artificial Intelligence Reinforcement Learning in Python (12.2024)

Creation Time	July 10, 2025, 7:59 a.m.
Last Access Time	July 11, 2025, 11:13 p.m.
File Size	4.2 GB
Keywords	12 Python Intelligence - Reinforcement Udemy 2024 Artificial Learning in
Total Requests	3
Total Files	780
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11 - Setting Up Your Environment (FAQ by Student Request)/2 -Anaconda Environment Setup.mp4 186.4 MB
4 - Markov Decision Proccesses/11 -Bellman Examples.mp4 87.1 MB
10 - Stock Trading Project with Reinforcement Learning/1 -Beginners, halt! Stop here if you skipped ahead.mp4 83.8 MB
12 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/3 -Proof that using Jupyter Notebook is the same as not using it.mp4 78.3 MB
8 - Approximation Methods/7 -Approximation Methods for Control Code.mp4 77.7 MB
2 - Return of the Multi-Armed Bandit/16 -Bayesian Bandits Thompson Sampling Theory (pt 2).mp4 74.5 MB
5 - Dynamic Programming/5 -Iterative Policy Evaluation in Code.mp4 68.4 MB
10 - Stock Trading Project with Reinforcement Learning/7 -Code pt 2.mp4 65.3 MB
6 - Monte Carlo/5 -Monte Carlo Control in Code.mp4 64.4 MB
1 - Welcome/5 -Warmup.mp4 62.6 MB
8 - Approximation Methods/5 -Approximation Methods for Prediction Code.mp4 62.3 MB
4 - Markov Decision Proccesses/5 -Markov Decision Processes (MDPs).mp4 61.7 MB
5 - Dynamic Programming/2 -Iterative Policy Evaluation.mp4 60.8 MB
5 - Dynamic Programming/10 -Policy Iteration in Code.mp4 56.4 MB
4 - Markov Decision Proccesses/12 -Optimal Policy and Optimal Value Function (pt 1).mp4 56.1 MB
2 - Return of the Multi-Armed Bandit/15 -Bayesian Bandits Thompson Sampling Theory (pt 1).mp4 55.9 MB
2 - Return of the Multi-Armed Bandit/12 -UCB1 Theory.mp4 55.5 MB
3 - High Level Overview of Reinforcement Learning/1 -What is Reinforcement Learning.mp4 54.6 MB
4 - Markov Decision Proccesses/2 -Gridworld.mp4 54.0 MB
10 - Stock Trading Project with Reinforcement Learning/9 -Code pt 4.mp4 52.9 MB
10 - Stock Trading Project with Reinforcement Learning/3 -Data and Environment.mp4 52.0 MB
2 - Return of the Multi-Armed Bandit/1 -Section Introduction The Explore-Exploit Dilemma.mp4 52.0 MB
6 - Monte Carlo/3 -Monte Carlo Policy Evaluation in Code.mp4 51.6 MB
5 - Dynamic Programming/11 -Policy Iteration in Windy Gridworld.mp4 51.4 MB
2 - Return of the Multi-Armed Bandit/2 -Applications of the Explore-Exploit Dilemma.mp4 51.2 MB
2 - Return of the Multi-Armed Bandit/25 -(Optional) Alternative Bandit Designs.mp4 50.3 MB
10 - Stock Trading Project with Reinforcement Learning/6 -Code pt 1.mp4 49.7 MB
2 - Return of the Multi-Armed Bandit/19 -Thompson Sampling With Gaussian Reward Theory.mp4 48.5 MB
8 - Approximation Methods/9 -CartPole Code.mp4 48.2 MB
6 - Monte Carlo/1 -Monte Carlo Intro.mp4 47.6 MB
6 - Monte Carlo/2 -Monte Carlo Policy Evaluation.mp4 47.1 MB
5 - Dynamic Programming/7 -Iterative Policy Evaluation for Windy Gridworld in Code.mp4 46.9 MB
5 - Dynamic Programming/4 -Gridworld in Code.mp4 46.8 MB
8 - Approximation Methods/3 -Feature Engineering.mp4 45.9 MB
5 - Dynamic Programming/13 -Value Iteration in Code.mp4 45.7 MB
7 - Temporal Difference Learning/5 -SARSA in Code.mp4 44.9 MB
10 - Stock Trading Project with Reinforcement Learning/4 -How to Model Q for Q-Learning.mp4 44.9 MB
5 - Dynamic Programming/8 -Policy Improvement.mp4 44.0 MB
11 - Setting Up Your Environment (FAQ by Student Request)/3 -How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4 43.9 MB
2 - Return of the Multi-Armed Bandit/8 -Comparing Different Epsilons.mp4 43.7 MB
2 - Return of the Multi-Armed Bandit/20 -Thompson Sampling With Gaussian Reward Code.mp4 43.4 MB
5 - Dynamic Programming/6 -Windy Gridworld in Code.mp4 41.5 MB
2 - Return of the Multi-Armed Bandit/7 -Epsilon-Greedy in Code.mp4 41.4 MB
3 - High Level Overview of Reinforcement Learning/2 -From Bandits to Full Reinforcement Learning.mp4 41.2 MB
6 - Monte Carlo/7 -Monte Carlo Control without Exploring Starts in Code.mp4 40.7 MB
14 - Appendix FAQ Finale/2 -BONUS.mp4 40.5 MB
1 - Welcome/2 -Course Outline and Big Picture.mp4 39.7 MB
4 - Markov Decision Proccesses/6 -Future Rewards.mp4 39.5 MB
13 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/2 -Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4 39.0 MB
7 - Temporal Difference Learning/7 -Q Learning in Code.mp4 38.5 MB
9 - Interlude Common Beginner Questions/1 -This Course vs. RL Book What's the Difference.mp4 38.2 MB
13 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/4 -Machine Learning and AI Prerequisite Roadmap (pt 2).mp4 37.6 MB
4 - Markov Decision Proccesses/1 -MDP Section Introduction.mp4 37.2 MB
6 - Monte Carlo/4 -Monte Carlo Control.mp4 35.6 MB
5 - Dynamic Programming/12 -Value Iteration.mp4 35.3 MB
5 - Dynamic Programming/1 -Dynamic Programming Section Introduction.mp4 34.7 MB
2 - Return of the Multi-Armed Bandit/24 -Bandit Summary, Real Data, and Online Learning.mp4 34.6 MB
8 - Approximation Methods/4 -Approximation Methods for Prediction.mp4 34.3 MB
1 - Welcome/1 -Introduction.mp4 34.2 MB
5 - Dynamic Programming/9 -Policy Iteration.mp4 34.2 MB
10 - Stock Trading Project with Reinforcement Learning/8 -Code pt 3.mp4 33.7 MB
2 - Return of the Multi-Armed Bandit/18 -Thompson Sampling Code.mp4 32.8 MB
4 - Markov Decision Proccesses/3 -Choosing Rewards.mp4 32.5 MB
7 - Temporal Difference Learning/3 -TD(0) Prediction in Code.mp4 32.4 MB
8 - Approximation Methods/2 -Linear Models for Reinforcement Learning.mp4 31.1 MB
2 - Return of the Multi-Armed Bandit/23 -Nonstationary Bandits.mp4 31.0 MB
13 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/3 -Machine Learning and AI Prerequisite Roadmap (pt 1).mp4 29.3 MB
2 - Return of the Multi-Armed Bandit/5 -Epsilon-Greedy Beginner's Exercise Prompt.mp4 28.7 MB
2 - Return of the Multi-Armed Bandit/3 -Epsilon-Greedy Theory.mp4 28.3 MB
4 - Markov Decision Proccesses/8 -The Bellman Equation (pt 1).mp4 27.8 MB
2 - Return of the Multi-Armed Bandit/22 -Why don't we just use a library.mp4 27.4 MB
2 - Return of the Multi-Armed Bandit/26 -Suggestion Box.mp4 27.2 MB
8 - Approximation Methods/8 -CartPole.mp4 26.9 MB
10 - Stock Trading Project with Reinforcement Learning/2 -Stock Trading Project Section Introduction.mp4 26.8 MB
4 - Markov Decision Proccesses/9 -The Bellman Equation (pt 2).mp4 26.7 MB
5 - Dynamic Programming/14 -Dynamic Programming Summary.mp4 25.1 MB
4 - Markov Decision Proccesses/10 -The Bellman Equation (pt 3).mp4 24.7 MB
2 - Return of the Multi-Armed Bandit/11 -Optimistic Initial Values Code.mp4 24.6 MB
12 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/1 -How to Code by Yourself (part 1).mp4 24.5 MB
2 - Return of the Multi-Armed Bandit/6 -Designing Your Bandit Program.mp4 24.5 MB
2 - Return of the Multi-Armed Bandit/9 -Optimistic Initial Values Theory.mp4 23.5 MB
6 - Monte Carlo/6 -Monte Carlo Control without Exploring Starts.mp4 23.4 MB
10 - Stock Trading Project with Reinforcement Learning/5 -Design of the Program.mp4 23.3 MB
2 - Return of the Multi-Armed Bandit/4 -Calculating a Sample Mean (pt 1).mp4 23.1 MB
11 - Setting Up Your Environment (FAQ by Student Request)/1 -Pre-Installation Check.mp4 22.7 MB
1 - Welcome/3 -Where to get the Code.mp4 22.7 MB
5 - Dynamic Programming/3 -Designing Your RL Program.mp4 22.3 MB
8 - Approximation Methods/1 -Approximation Methods Section Introduction.mp4 22.1 MB
4 - Markov Decision Proccesses/4 -The Markov Property.mp4 21.8 MB
8 - Approximation Methods/11 -Approximation Methods Section Summary.mp4 21.8 MB
2 - Return of the Multi-Armed Bandit/14 -UCB1 Code.mp4 20.7 MB
7 - Temporal Difference Learning/6 -Q Learning.mp4 19.8 MB
4 - Markov Decision Proccesses/13 -Optimal Policy and Optimal Value Function (pt 2).mp4 18.7 MB
4 - Markov Decision Proccesses/7 -Value Functions.mp4 18.5 MB
13 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/1 -How to Succeed in this Course (Long Version).mp4 18.3 MB
2 - Return of the Multi-Armed Bandit/17 -Thompson Sampling Beginner's Exercise Prompt.mp4 17.9 MB
8 - Approximation Methods/6 -Approximation Methods for Control.mp4 17.6 MB
8 - Approximation Methods/10 -Approximation Methods Exercise.mp4 17.5 MB
1 - Welcome/4 -How to Succeed in this Course.mp4 16.3 MB
7 - Temporal Difference Learning/4 -SARSA.mp4 16.2 MB
7 - Temporal Difference Learning/2 -TD(0) Prediction.mp4 15.8 MB
10 - Stock Trading Project with Reinforcement Learning/10 -Stock Trading Project Discussion.mp4 15.8 MB
12 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/2 -How to Code by Yourself (part 2).mp4 14.8 MB
7 - Temporal Difference Learning/1 -Temporal Difference Introduction.mp4 14.4 MB
4 - Markov Decision Proccesses/14 -MDP Summary.mp4 14.3 MB
2 - Return of the Multi-Armed Bandit/10 -Optimistic Initial Values Beginner's Exercise Prompt.mp4 13.8 MB
2 - Return of the Multi-Armed Bandit/13 -UCB1 Beginner's Exercise Prompt.mp4 12.7 MB
6 - Monte Carlo/8 -Monte Carlo Summary.mp4 11.4 MB
7 - Temporal Difference Learning/8 -TD Learning Section Summary.mp4 10.0 MB
12 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/4 -Python 2 vs Python 3.mp4 7.8 MB
2 - Return of the Multi-Armed Bandit/21 -Exercise on Gaussian Rewards.mp4 6.8 MB
14 - Appendix FAQ Finale/1 -What is the Appendix.mp4 5.5 MB
13 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/subtitles/2 -Is this for Beginners or Experts Academic or Practical Fast or slow-paced.fr_FR.vtt 31.8 KB
13 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/subtitles/2 -Is this for Beginners or Experts Academic or Practical Fast or slow-paced.de_DE.vtt 30.9 KB
13 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/subtitles/2 -Is this for Beginners or Experts Academic or Practical Fast or slow-paced.pt_BR.vtt 29.9 KB
13 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/subtitles/2 -Is this for Beginners or Experts Academic or Practical Fast or slow-paced.es_ES.vtt 29.8 KB
13 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/subtitles/2 -Is this for Beginners or Experts Academic or Practical Fast or slow-paced.it_IT.vtt 29.6 KB
13 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/2 -Is this for Beginners or Experts Academic or Practical Fast or slow-paced.vtt 27.8 KB
4 - Markov Decision Proccesses/subtitles/11 -Bellman Examples.fr_FR.vtt 27.5 KB
4 - Markov Decision Proccesses/subtitles/11 -Bellman Examples.de_DE.vtt 27.3 KB
12 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/1 -How to Code by Yourself (part 1).vtt 27.3 KB
4 - Markov Decision Proccesses/subtitles/11 -Bellman Examples.es_ES.vtt 25.8 KB
12 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/subtitles/1 -How to Code by Yourself (part 1).fr_FR.vtt 25.7 KB
4 - Markov Decision Proccesses/subtitles/11 -Bellman Examples.pt_BR.vtt 25.6 KB
4 - Markov Decision Proccesses/subtitles/11 -Bellman Examples.it_IT.vtt 25.6 KB
12 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/subtitles/1 -How to Code by Yourself (part 1).de_DE.vtt 24.7 KB
12 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/subtitles/1 -How to Code by Yourself (part 1).pt_BR.vtt 24.2 KB
12 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/subtitles/1 -How to Code by Yourself (part 1).es_ES.vtt 24.1 KB
4 - Markov Decision Proccesses/11 -Bellman Examples.vtt 24.1 KB
13 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/subtitles/4 -Machine Learning and AI Prerequisite Roadmap (pt 2).fr_FR.vtt 23.9 KB
2 - Return of the Multi-Armed Bandit/subtitles/16 -Bayesian Bandits Thompson Sampling Theory (pt 2).fr_FR.vtt 23.8 KB
12 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/subtitles/1 -How to Code by Yourself (part 1).it_IT.vtt 23.7 KB
2 - Return of the Multi-Armed Bandit/subtitles/16 -Bayesian Bandits Thompson Sampling Theory (pt 2).de_DE.vtt 22.8 KB
13 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/subtitles/4 -Machine Learning and AI Prerequisite Roadmap (pt 2).de_DE.vtt 22.5 KB
13 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/subtitles/4 -Machine Learning and AI Prerequisite Roadmap (pt 2).es_ES.vtt 22.4 KB
13 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/subtitles/4 -Machine Learning and AI Prerequisite Roadmap (pt 2).pt_BR.vtt 22.3 KB
13 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/subtitles/4 -Machine Learning and AI Prerequisite Roadmap (pt 2).it_IT.vtt 22.2 KB
2 - Return of the Multi-Armed Bandit/subtitles/16 -Bayesian Bandits Thompson Sampling Theory (pt 2).it_IT.vtt 22.1 KB
2 - Return of the Multi-Armed Bandit/subtitles/16 -Bayesian Bandits Thompson Sampling Theory (pt 2).es_ES.vtt 22.0 KB
2 - Return of the Multi-Armed Bandit/subtitles/16 -Bayesian Bandits Thompson Sampling Theory (pt 2).pt_BR.vtt 21.8 KB
5 - Dynamic Programming/subtitles/2 -Iterative Policy Evaluation.fr_FR.vtt 21.2 KB
2 - Return of the Multi-Armed Bandit/16 -Bayesian Bandits Thompson Sampling Theory (pt 2).vtt 20.7 KB
5 - Dynamic Programming/subtitles/2 -Iterative Policy Evaluation.de_DE.vtt 20.5 KB
10 - Stock Trading Project with Reinforcement Learning/subtitles/1 -Beginners, halt! Stop here if you skipped ahead.fr_FR.vtt 20.4 KB
11 - Setting Up Your Environment (FAQ by Student Request)/subtitles/2 -Anaconda Environment Setup.fr_FR.vtt 20.3 KB
13 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/4 -Machine Learning and AI Prerequisite Roadmap (pt 2).vtt 20.2 KB
5 - Dynamic Programming/subtitles/2 -Iterative Policy Evaluation.es_ES.vtt 20.1 KB
2 - Return of the Multi-Armed Bandit/subtitles/12 -UCB1 Theory.fr_FR.vtt 19.9 KB
5 - Dynamic Programming/subtitles/2 -Iterative Policy Evaluation.it_IT.vtt 19.8 KB
11 - Setting Up Your Environment (FAQ by Student Request)/subtitles/2 -Anaconda Environment Setup.de_DE.vtt 19.8 KB
5 - Dynamic Programming/subtitles/2 -Iterative Policy Evaluation.pt_BR.vtt 19.7 KB
10 - Stock Trading Project with Reinforcement Learning/subtitles/1 -Beginners, halt! Stop here if you skipped ahead.de_DE.vtt 19.7 KB
4 - Markov Decision Proccesses/subtitles/5 -Markov Decision Processes (MDPs).fr_FR.vtt 19.6 KB
2 - Return of the Multi-Armed Bandit/subtitles/12 -UCB1 Theory.de_DE.vtt 19.5 KB
4 - Markov Decision Proccesses/subtitles/5 -Markov Decision Processes (MDPs).de_DE.vtt 19.4 KB
10 - Stock Trading Project with Reinforcement Learning/subtitles/1 -Beginners, halt! Stop here if you skipped ahead.es_ES.vtt 19.1 KB
10 - Stock Trading Project with Reinforcement Learning/subtitles/1 -Beginners, halt! Stop here if you skipped ahead.pt_BR.vtt 19.0 KB
11 - Setting Up Your Environment (FAQ by Student Request)/subtitles/2 -Anaconda Environment Setup.es_ES.vtt 18.9 KB
10 - Stock Trading Project with Reinforcement Learning/subtitles/1 -Beginners, halt! Stop here if you skipped ahead.it_IT.vtt 18.9 KB
2 - Return of the Multi-Armed Bandit/subtitles/12 -UCB1 Theory.it_IT.vtt 18.8 KB
2 - Return of the Multi-Armed Bandit/subtitles/12 -UCB1 Theory.es_ES.vtt 18.7 KB
11 - Setting Up Your Environment (FAQ by Student Request)/subtitles/2 -Anaconda Environment Setup.pt_BR.vtt 18.7 KB
11 - Setting Up Your Environment (FAQ by Student Request)/subtitles/2 -Anaconda Environment Setup.it_IT.vtt 18.6 KB
1 - Welcome/subtitles/5 -Warmup.fr_FR.vtt 18.5 KB
5 - Dynamic Programming/2 -Iterative Policy Evaluation.vtt 18.5 KB
4 - Markov Decision Proccesses/subtitles/5 -Markov Decision Processes (MDPs).es_ES.vtt 18.5 KB
2 - Return of the Multi-Armed Bandit/subtitles/12 -UCB1 Theory.pt_BR.vtt 18.4 KB
4 - Markov Decision Proccesses/subtitles/5 -Markov Decision Processes (MDPs).it_IT.vtt 18.3 KB
4 - Markov Decision Proccesses/subtitles/5 -Markov Decision Processes (MDPs).pt_BR.vtt 18.1 KB
1 - Welcome/subtitles/5 -Warmup.de_DE.vtt 18.1 KB
10 - Stock Trading Project with Reinforcement Learning/1 -Beginners, halt! Stop here if you skipped ahead.vtt 18.0 KB
2 - Return of the Multi-Armed Bandit/12 -UCB1 Theory.vtt 17.4 KB
11 - Setting Up Your Environment (FAQ by Student Request)/2 -Anaconda Environment Setup.vtt 17.4 KB
1 - Welcome/subtitles/5 -Warmup.es_ES.vtt 17.2 KB
4 - Markov Decision Proccesses/5 -Markov Decision Processes (MDPs).vtt 17.2 KB
1 - Welcome/subtitles/5 -Warmup.it_IT.vtt 17.2 KB
4 - Markov Decision Proccesses/subtitles/2 -Gridworld.fr_FR.vtt 17.1 KB
1 - Welcome/subtitles/5 -Warmup.pt_BR.vtt 17.0 KB
4 - Markov Decision Proccesses/subtitles/2 -Gridworld.de_DE.vtt 17.0 KB
2 - Return of the Multi-Armed Bandit/subtitles/15 -Bayesian Bandits Thompson Sampling Theory (pt 1).fr_FR.vtt 16.8 KB
12 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/2 -How to Code by Yourself (part 2).vtt 16.7 KB
11 - Setting Up Your Environment (FAQ by Student Request)/3 -How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.vtt 16.6 KB
1 - Welcome/5 -Warmup.vtt 16.4 KB
5 - Dynamic Programming/subtitles/5 -Iterative Policy Evaluation in Code.fr_FR.vtt 16.4 KB
2 - Return of the Multi-Armed Bandit/subtitles/15 -Bayesian Bandits Thompson Sampling Theory (pt 1).de_DE.vtt 16.4 KB
4 - Markov Decision Proccesses/subtitles/2 -Gridworld.es_ES.vtt 16.3 KB
4 - Markov Decision Proccesses/subtitles/2 -Gridworld.it_IT.vtt 16.1 KB
13 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/subtitles/3 -Machine Learning and AI Prerequisite Roadmap (pt 1).fr_FR.vtt 16.0 KB
5 - Dynamic Programming/subtitles/5 -Iterative Policy Evaluation in Code.de_DE.vtt 16.0 KB
5 - Dynamic Programming/subtitles/4 -Gridworld in Code.fr_FR.vtt 15.9 KB
5 - Dynamic Programming/subtitles/4 -Gridworld in Code.de_DE.vtt 15.9 KB
2 - Return of the Multi-Armed Bandit/subtitles/15 -Bayesian Bandits Thompson Sampling Theory (pt 1).es_ES.vtt 15.8 KB
10 - Stock Trading Project with Reinforcement Learning/subtitles/3 -Data and Environment.fr_FR.vtt 15.7 KB
4 - Markov Decision Proccesses/subtitles/2 -Gridworld.pt_BR.vtt 15.7 KB
5 - Dynamic Programming/subtitles/5 -Iterative Policy Evaluation in Code.it_IT.vtt 15.7 KB
5 - Dynamic Programming/subtitles/5 -Iterative Policy Evaluation in Code.es_ES.vtt 15.7 KB
2 - Return of the Multi-Armed Bandit/subtitles/15 -Bayesian Bandits Thompson Sampling Theory (pt 1).it_IT.vtt 15.6 KB
11 - Setting Up Your Environment (FAQ by Student Request)/subtitles/3 -How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.fr_FR.vtt 15.4 KB
2 - Return of the Multi-Armed Bandit/subtitles/15 -Bayesian Bandits Thompson Sampling Theory (pt 1).pt_BR.vtt 15.4 KB
13 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/subtitles/3 -Machine Learning and AI Prerequisite Roadmap (pt 1).de_DE.vtt 15.4 KB
12 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/subtitles/2 -How to Code by Yourself (part 2).fr_FR.vtt 15.3 KB
10 - Stock Trading Project with Reinforcement Learning/subtitles/3 -Data and Environment.de_DE.vtt 15.3 KB
5 - Dynamic Programming/subtitles/4 -Gridworld in Code.es_ES.vtt 15.3 KB
13 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/subtitles/3 -Machine Learning and AI Prerequisite Roadmap (pt 1).es_ES.vtt 15.3 KB
5 - Dynamic Programming/subtitles/5 -Iterative Policy Evaluation in Code.pt_BR.vtt 15.2 KB
12 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/subtitles/2 -How to Code by Yourself (part 2).de_DE.vtt 15.2 KB
13 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/subtitles/3 -Machine Learning and AI Prerequisite Roadmap (pt 1).it_IT.vtt 15.2 KB
13 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/subtitles/3 -Machine Learning and AI Prerequisite Roadmap (pt 1).pt_BR.vtt 15.2 KB
4 - Markov Decision Proccesses/2 -Gridworld.vtt 15.2 KB
11 - Setting Up Your Environment (FAQ by Student Request)/subtitles/3 -How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.de_DE.vtt 15.1 KB
2 - Return of the Multi-Armed Bandit/subtitles/19 -Thompson Sampling With Gaussian Reward Theory.fr_FR.vtt 15.0 KB
5 - Dynamic Programming/subtitles/4 -Gridworld in Code.it_IT.vtt 15.0 KB
10 - Stock Trading Project with Reinforcement Learning/subtitles/3 -Data and Environment.es_ES.vtt 14.9 KB
5 - Dynamic Programming/subtitles/8 -Policy Improvement.fr_FR.vtt 14.9 KB
8 - Approximation Methods/subtitles/3 -Feature Engineering.fr_FR.vtt 14.9 KB
5 - Dynamic Programming/subtitles/4 -Gridworld in Code.pt_BR.vtt 14.8 KB
10 - Stock Trading Project with Reinforcement Learning/subtitles/3 -Data and Environment.pt_BR.vtt 14.8 KB
2 - Return of the Multi-Armed Bandit/15 -Bayesian Bandits Thompson Sampling Theory (pt 1).vtt 14.7 KB
10 - Stock Trading Project with Reinforcement Learning/subtitles/3 -Data and Environment.it_IT.vtt 14.7 KB
6 - Monte Carlo/subtitles/2 -Monte Carlo Policy Evaluation.fr_FR.vtt 14.7 KB
2 - Return of the Multi-Armed Bandit/subtitles/19 -Thompson Sampling With Gaussian Reward Theory.de_DE.vtt 14.6 KB
13 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/subtitles/1 -How to Succeed in this Course (Long Version).fr_FR.vtt 14.6 KB
11 - Setting Up Your Environment (FAQ by Student Request)/subtitles/3 -How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.pt_BR.vtt 14.5 KB
12 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/subtitles/2 -How to Code by Yourself (part 2).pt_BR.vtt 14.5 KB
12 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/subtitles/2 -How to Code by Yourself (part 2).es_ES.vtt 14.5 KB
11 - Setting Up Your Environment (FAQ by Student Request)/subtitles/3 -How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.es_ES.vtt 14.5 KB
6 - Monte Carlo/subtitles/2 -Monte Carlo Policy Evaluation.de_DE.vtt 14.5 KB
5 - Dynamic Programming/subtitles/8 -Policy Improvement.de_DE.vtt 14.5 KB
12 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/subtitles/2 -How to Code by Yourself (part 2).it_IT.vtt 14.3 KB
8 - Approximation Methods/subtitles/3 -Feature Engineering.de_DE.vtt 14.2 KB
13 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/subtitles/1 -How to Succeed in this Course (Long Version).de_DE.vtt 14.2 KB
5 - Dynamic Programming/4 -Gridworld in Code.vtt 14.2 KB
5 - Dynamic Programming/5 -Iterative Policy Evaluation in Code.vtt 14.2 KB
2 - Return of the Multi-Armed Bandit/subtitles/25 -(Optional) Alternative Bandit Designs.fr_FR.vtt 14.2 KB
2 - Return of the Multi-Armed Bandit/subtitles/19 -Thompson Sampling With Gaussian Reward Theory.es_ES.vtt 14.2 KB
11 - Setting Up Your Environment (FAQ by Student Request)/subtitles/3 -How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.it_IT.vtt 14.2 KB
13 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/3 -Machine Learning and AI Prerequisite Roadmap (pt 1).vtt 14.1 KB
8 - Approximation Methods/subtitles/3 -Feature Engineering.es_ES.vtt 14.0 KB
6 - Monte Carlo/subtitles/2 -Monte Carlo Policy Evaluation.es_ES.vtt 14.0 KB
2 - Return of the Multi-Armed Bandit/subtitles/19 -Thompson Sampling With Gaussian Reward Theory.pt_BR.vtt 13.9 KB
2 - Return of the Multi-Armed Bandit/subtitles/19 -Thompson Sampling With Gaussian Reward Theory.it_IT.vtt 13.9 KB
6 - Monte Carlo/subtitles/2 -Monte Carlo Policy Evaluation.it_IT.vtt 13.9 KB
5 - Dynamic Programming/subtitles/8 -Policy Improvement.es_ES.vtt 13.9 KB
8 - Approximation Methods/subtitles/3 -Feature Engineering.it_IT.vtt 13.9 KB
12 - Extra Help With Python Coding for Beginners (FAQ by Student Request)/subtitles/3 -Proof that using Jupyter Notebook is the same as not using it.fr_FR.vtt 13.9 KB
5 - Dynamic Programming/subtitles/8 -Policy Improvement.it_IT.vtt 13.8 KB
10 - Stock Trading Project with Reinforcement Learning/3 -Data and Environment.vtt 13.8 KB
13 - Effective Learning Strategies for Machine Learning (FAQ by Student Request)/subtitles/1 -How to Succeed in this Course (Long Version).pt_BR.vtt 13.7 KB
2 - Return of the Multi-Armed Bandit/subtitles/25 -(Optional) Alternative Bandit Designs.de_DE.vtt 13.7 KB
8 - Approximation Methods/subtitles/3 -Feature Engineering.pt_BR.vtt 13.6 KB
5 - Dynamic Programming/subtitles/8 -Policy Improvement.pt_BR.vtt 13.6 KB
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2 - Return of the Multi-Armed Bandit/subtitles/21 -Exercise on Gaussian Rewards.fr_FR.vtt 1.6 KB
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1 - Welcome/3 -Github Link.url 82 bytes

Udemy - Artificial Intelligence Reinforcement Learning in Python (12.2024)

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