Stanford CS221 - Artificial Intelligence: Principles and Techniques - Autumn 2021

Stanford CS221 - Artificial Intelligence: Principles and Techniques - Autumn 2021

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General Intro | Stanford CS221: Artificial Intelligence: Principles and Techniques (Autumn 2021)

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General Intro | Stanford CS221: Artificial Intelligence: Principles and Techniques (Autumn 2021)

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Stanford CS221 - Artificial Intelligence: Principles and Techniques - Autumn 2021

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  1. 1 General Intro | Stanford CS221: Artificial Intelligence: Principles and Techniques (Autumn 2021)
  2. 2 AI History | Stanford CS221: AI (Autumn 2021)
  3. 3 Artificial Intelligence Today | Stanford CS221: AI (Autumn 2021)
  4. 4 Artificial Intelligence and Machine Learning 1 - Overview | Stanford CS221: AI (Autumn 2021)
  5. 5 Artificial Intelligence & Machine Learning 2 - Linear Regression | Stanford CS221: AI (Autumn 2021)
  6. 6 Artificial Intelligence & Machine learning 3 - Linear Classification | Stanford CS221 (Autumn 2021)
  7. 7 Artificial Intelligence & Machine Learning 4 - Stochastic Gradient Descent | Stanford CS221 (2021)
  8. 8 Artificial Intelligence and Machine Learning 5 - Group DRO | Stanford CS221: AI (Autumn 2021)
  9. 9 Artificial Intelligence & Machine Learning 6 - Non Linear Features | Stanford CS221: AI(Autumn 2021)
  10. 10 Artificial Intelligence & Machine Learning 7 - Feature Templates | Stanford CS221: AI (Autumn 2021)
  11. 11 Artificial Intelligence & Machine Learning 8 - Neural Networks | Stanford CS221: AI (Autumn 2021)
  12. 12 Machine Learning 9 - Backpropagation | Stanford CS221: AI (Autumn 2021)
  13. 13 Machine Learning 10 - Differentiable Programming | Stanford CS221: AI (Autumn 2021)
  14. 14 Artificial Intelligence & Machine Learning 11 - Generalization | Stanford CS221: AI (Autumn 2021)
  15. 15 Artificial Intelligence & Machine Learning 12 - Best Practices | Stanford CS221: AI (Autumn 2021)
  16. 16 Machine Learning 13 - K-means | Stanford CS221: AI (Autumn 2021)
  17. 17 Search 1 - Dynamic Programming, Uniform Cost Search | Stanford CS221: AI (Autumn 2019)
  18. 18 Search 2 - A* | Stanford CS221: Artificial Intelligence (Autumn 2019)
  19. 19 Markov Decision Processes 1 - Value Iteration | Stanford CS221: AI (Autumn 2019)
  20. 20 Markov Decision Processes 2 - Reinforcement Learning | Stanford CS221: AI (Autumn 2019)
  21. 21 Game Playing 1 - Minimax, Alpha-beta Pruning | Stanford CS221: AI (Autumn 2019)
  22. 22 Game Playing 2 - TD Learning, Game Theory | Stanford CS221: Artificial Intelligence (Autumn 2019)
  23. 23 Constraint Satisfaction Problems (CSPs) 1 - Overview | Stanford CS221: AI (Autumn 2021)
  24. 24 Constraint Satisfaction Problems (CSPs) 2 - Definitions | Stanford CS221: AI (Autumn 2021)
  25. 25 Constraint Satisfaction Problems (CSPs) 3 - Examples | Stanford CS221: AI (Autumn 2021)
  26. 26 Constraint Satisfaction Problems (CSPs) 4 - Dynamic Ordering | Stanford CS221: AI (Autumn 2021)
  27. 27 Constraint Satisfaction Problems (CSPs) 5 - Arc Consistency | Stanford CS221: AI (Autumn 2021)
  28. 28 Constraint Satisfaction Problems (CSPs) 6 - Beam Search | Stanford CS221: AI (Autumn 2021)
  29. 29 Constraint Satisfaction Problems (CSPs) 7 - Local Search | Stanford CS221: AI (Autumn 2021)
  30. 30 Markov Networks 1 - Overview | Stanford CS221: Artificial Intelligence (Autumn 2021)
  31. 31 Markov Networks 2 - Gibbs Sampling | Stanford CS221: AI (Autumn 2021)
  32. 32 Bayesian Networks 1 - Overview | Stanford CS221: AI (Autumn 2021)
  33. 33 Bayesian Networks 2 - Definition | Stanford CS221: AI (Autumn 2021)
  34. 34 Bayesian Networks 3 - Probabilistic Programming | Stanford CS221: AI (Autumn 2021)
  35. 35 Bayesian Networks 4 - Probabilistic Inference | Stanford CS221: AI (Autumn 2021)
  36. 36 Bayesian Networks 5 - Forward-backward Algorithm | Stanford CS221: AI (Autumn 2021)
  37. 37 Bayesian Networks 6 - Particle Filtering | Stanford CS221: AI (Autumn 2021)
  38. 38 Bayesian Networks 7 - Supervised Learning | Stanford CS221: AI (Autumn 2021)
  39. 39 Bayesian Networks 8 - Smoothing | Stanford CS221: AI (Autumn 2021)
  40. 40 Bayesian Networks 9 - EM Algorithm | Stanford CS221: AI (Autumn 2021)
  41. 41 Logic 1 - Overview: Logic Based Models | Stanford CS221: AI (Autumn 2021)
  42. 42 Logic 2 - Propositional Logic Syntax | Stanford CS221: AI (Autumn 2021)
  43. 43 Logic 3 - Propositional Logic Semantics | Stanford CS221: AI (Autumn 2021)
  44. 44 Logic 4 - Inference Rules | Stanford CS221: AI (Autumn 2021)
  45. 45 Logic 5 - Propositional Modus Ponens | Stanford CS221: AI (Autumn 2021)
  46. 46 Logic 6 - Propositional Resolutions | Stanford CS221: AI (Autumn 2021)
  47. 47 Logic 7 - First Order Logic | Stanford CS221: AI (Autumn 2021)
  48. 48 Logic 8 - First Order Modus Ponens | Stanford CS221: Artificial Intelligence (Autumn 2021)
  49. 49 Logic 9 - First Order Resolution | Stanford CS221: AI (Autumn 2021)
  50. 50 Logic 10 - Recap | Stanford CS221: Artificial Intelligence (Autumn 2021)
  51. 51 AI and Law I Mariano-Florentino Cuéllar, President of the Carnegie Endowment for International Peace
  52. 52 Stanford Fireside Talks: Robustness in Machine Learning I Robust Machine Learning
  53. 53 Fireside Talks: State of Robotics I Automation and Robotics Engineering Lectures - Stanford
  54. 54 Stanford Talk: Inequality in Healthcare, AI & Data Science to Reduce Inequality - Improve Healthcare
  55. 55 Fireside Talks: Artificial Intelligence (AI) and Language
  56. 56 General Conclusion | Stanford CS221: AI (Autumn 2021)
  57. 57 Stanford CS221 I Externalities and Dual-Use Technologies I 2023
  58. 58 Stanford CS221 I The AI Alignment Problem: Reward Hacking & Negative Side Effects I 2023
  59. 59 Stanford CS221 I Encoding Human Values I 2023
  60. 60 Stanford CS221 I Algorithms and Distribution I 2023

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