spring lecture

Pick anything below and it plays in the bar at the foot of the window — and keeps playing while you go on browsing the directory.

1. 1▶Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 19: Model-Based RLStanford OnlineNotes
   +Watch later
2. 2▶Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 18: RL Policy OptimizationStanford OnlineNotes
   +Watch later
3. 3▶Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 17: RL Value-Based MethodsStanford OnlineNotes
   +Watch later
4. 4▶Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 16: Fundamentals of RLStanford OnlineNotes
   +Watch later
5. 5▶Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 15: Imitation LearningStanford OnlineNotes
   +Watch later
6. 6▶Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 14: Intro to IL and RLStanford OnlineNotes
   +Watch later
7. 7▶Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 13: Intro to LearningStanford OnlineNotes
   +Watch later
8. 8▶Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 12: Feasibility of MPCStanford OnlineNotes
   +Watch later
9. 9▶Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 11: Introduction to MPCStanford OnlineNotes
   +Watch later
10. 10▶Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 10: Reachibility AnalysisStanford OnlineNotes
    +Watch later
11. 11▶Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 9: Stochastic Dyn. ProgramStanford OnlineNotes
    +Watch later
12. 12▶AStanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 8: LQR-Style AlgorithmsStanford OnlineNotes
    +Watch later
13. 13▶Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 7: Dynamic ProgrammingStanford OnlineNotes
    +Watch later
14. 14▶Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 6: Direct MethodsStanford OnlineNotes
    +Watch later
15. 15▶Stanford AA203 Optimal and Learning-Based Control | Spring 2026 | Lecture 5: Computational MethodsStanford OnlineNotes
    +Watch later
16. 16▶Stanford CS231N Deep Learning for Computer Vision | Spring 2025 | Lecture 1: IntroductionStanford CS231N Deep Learning for Computer Vision I 2025Notes
    +Watch later
17. 17▶Stanford CS231N | Spring 2025 | Lecture 2: Image Classification with Linear ClassifiersStanford CS231N Deep Learning for Computer Vision I 2025Notes
    +Watch later
18. 18▶Stanford CS231N | Spring 2025 | Lecture 3: Regularization and OptimizationStanford CS231N Deep Learning for Computer Vision I 2025Notes
    +Watch later
19. 19▶Stanford CS231N | Spring 2025 | Lecture 4: Neural Networks and BackpropagationStanford CS231N Deep Learning for Computer Vision I 2025Notes
    +Watch later
20. 20▶Stanford CS231N | Spring 2025 | Lecture 5: Image Classification with CNNsStanford CS231N Deep Learning for Computer Vision I 2025Notes
    +Watch later
21. 21▶Stanford CS231N Deep Learning for Computer Vision | Spring 2025 | Lecture 6: CNN ArchitecturesStanford CS231N Deep Learning for Computer Vision I 2025Notes
    +Watch later
22. 22▶Stanford CS231N | Spring 2025 | Lecture 7: Recurrent Neural NetworksStanford CS231N Deep Learning for Computer Vision I 2025Notes
    +Watch later
23. 23▶Stanford CS231N | Spring 2025 | Lecture 8: Attention and TransformersStanford CS231N Deep Learning for Computer Vision I 2025Notes
    +Watch later
24. 24▶Stanford CS231N | Spring 2025 | Lecture 9: Object Detection, Image Segmentation, VisualizingStanford CS231N Deep Learning for Computer Vision I 2025Notes
    +Watch later
25. 25▶Stanford CS231N | Spring 2025 | Lecture 11: Large Scale Distributed TrainingStanford CS231N Deep Learning for Computer Vision I 2025Notes
    +Watch later
26. 26▶Stanford CS231N | Spring 2025 | Lecture 12: Self-Supervised LearningStanford CS231N Deep Learning for Computer Vision I 2025Notes
    +Watch later
27. 27▶Stanford CS231N Deep Learning for Computer Vision | Spring 2025 | Lecture 13: Generative Models 1Stanford CS231N Deep Learning for Computer Vision I 2025Notes
    +Watch later
28. 28▶Stanford CS231N Deep Learning for Computer Vision | Spring 2025 | Lecture 14: Generative Models 2Stanford CS231N Deep Learning for Computer Vision I 2025Notes
    +Watch later
29. 29▶Stanford CS231N Deep Learning for Computer Vision | Spring 2025 | Lecture 15: 3D VisionStanford CS231N Deep Learning for Computer Vision I 2025Notes
    +Watch later
30. 30▶Stanford CS231N Deep Learning for Computer Vision | Spring 2025 | Lecture 10: Video UnderstandingStanford CS231N Deep Learning for Computer Vision I 2025Notes
    +Watch later
31. 31▶Stanford CS224N: NLP w/ DL | Spring 2024 | Lecture 14 - Reasoning and Agents by Shikhar MurtyStanford CS224N Natural Language Processing with Deep Learning I Spring 2024 I Professor Christopher ManningNotes
    +Watch later
32. 32▶Stanford CS224N: NLP w/ DL| Spring 2024 | Lecture 13 - Brain-Computer Interfaces, Chaofei FanStanford CS224N Natural Language Processing with Deep Learning I Spring 2024 I Professor Christopher ManningNotes
    +Watch later
33. 33▶Stanford CS224N: NLP w/ DL | Spring 2024 | Lecture 12 - Efficient Training, Shikhar MurtyStanford CS224N Natural Language Processing with Deep Learning I Spring 2024 I Professor Christopher ManningNotes
    +Watch later
34. 34▶Stanford CS224N: NLP with Deep Learning | Spring 2024 | Lecture 11 - Benchmarking by Yann DuboisStanford CS224N Natural Language Processing with Deep Learning I Spring 2024 I Professor Christopher ManningNotes
    +Watch later
35. 35▶Stanford CS224N: NLP with Deep Learning | Spring 2024 | Lecture 10 - Post-training by Archit SharmaStanford CS224N Natural Language Processing with Deep Learning I Spring 2024 I Professor Christopher ManningNotes
    +Watch later
36. 36▶Stanford CS224N: NLP w/ DL | Spring 2024 | Lecture 7 - Attention, Final Projects and LLM IntroStanford CS224N Natural Language Processing with Deep Learning I Spring 2024 I Professor Christopher ManningNotes
    +Watch later
37. 37▶Stanford CS224N: NLP with Deep Learning | Spring 2024 | Lecture 6 - Sequence to Sequence ModelsStanford CS224N Natural Language Processing with Deep Learning I Spring 2024 I Professor Christopher ManningNotes
    +Watch later
38. 38▶Stanford CS224N: NLP with Deep Learning | Spring 2024 | Lecture 5 - Recurrent Neural NetworksStanford CS224N Natural Language Processing with Deep Learning I Spring 2024 I Professor Christopher ManningNotes
    +Watch later
39. 39▶Stanford CS224N: NLP with Deep Learning | Spring 2024 | Lecture 4 - Dependency ParsingStanford CS224N Natural Language Processing with Deep Learning I Spring 2024 I Professor Christopher ManningNotes
    +Watch later
40. 40▶Stanford CS224N: NLP with Deep Learning | Spring 2024 | Lecture 3 - Backpropagation, Neural NetworkStanford CS224N Natural Language Processing with Deep Learning I Spring 2024 I Professor Christopher ManningNotes
    +Watch later
41. 41▶Stanford CS224N: NLP with Deep Learning | Spring 2024 | Lecture 2 - Word Vectors and Language ModelsStanford CS224N Natural Language Processing with Deep Learning I Spring 2024 I Professor Christopher ManningNotes
    +Watch later
42. 42▶Stanford CS224N: NLP with Deep Learning | Spring 2024 | Lecture 1 - Intro and Word VectorsStanford CS224N Natural Language Processing with Deep Learning I Spring 2024 I Professor Christopher ManningNotes
    +Watch later
43. 43▶6.8210 Spring 2024 Lecture 24: Imitation learning / Foundation models / Course wrap-upunderactuatedNotes
    +Watch later
44. 44▶6.8210 Spring 2024 Lecture 23: Feedback motion planningunderactuatedNotes
    +Watch later
45. 45▶6.8210 Spring 2024 Lecture 22: Output feedbackunderactuatedNotes
    +Watch later
46. 46▶6.8210 Spring 2024 Lecture 21: Robust Control & Policy SearchunderactuatedNotes
    +Watch later
47. 47▶6.8210 Spring 2024 Lecture 20: Stochastic ControlunderactuatedNotes
    +Watch later
48. 48▶6.8210 Spring 2024 Lecture 19: Stochastic dynamicsunderactuatedNotes
    +Watch later
49. 49▶6.8210 Spring 2024 Lecture 18: Sampling-based (kinodynamic) motion planningunderactuatedNotes
    +Watch later
50. 50▶6.8210 Spring 2024 Lecture 17: Mixed-discrete (combinatorial) and continuous optimizationunderactuatedNotes
    +Watch later