lecture introduction

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1. 1▶Sal Khan discusses MIT OpenCourseWareMIT OpenCourseWareNotes
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2. 2▶Sal Khan discusses MIT OpenCourseWareMIT OpenCourseWareNotes
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3. 3▶Should the Government Support the Lottery?MIT OpenCourseWareNotes
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4. 4▶Should the Government Support the Lottery?MIT OpenCourseWareNotes
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5. 5▶Lecture 4: Smart Contracts as a Solution to a Coordination ProblemMIT OpenCourseWareNotes
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6. 6▶Lecture 4: Smart Contracts as a Solution to a Coordination ProblemMIT OpenCourseWareNotes
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7. 7▶Lecture 10: Designs of Financial Infrastructure Utilizing EncryptionMIT OpenCourseWareNotes
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8. 8▶Lecture 10: Designs of Financial Infrastructure Utilizing EncryptionMIT OpenCourseWareNotes
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9. 9▶Lecture 7: Stochastic Financial NetworksMIT OpenCourseWareNotes
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10. 10▶Lecture 7: Stochastic Financial NetworksMIT OpenCourseWareNotes
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11. 11▶Lecture 8: Mechanism Design and Incentives vs. Protocols and Notions of TrustMIT OpenCourseWareNotes
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12. 12▶Lecture 8: Mechanism Design and Incentives vs. Protocols and Notions of TrustMIT OpenCourseWareNotes
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13. 13▶Lecture 3: Distributed Ledger as a Solution to an Information ProblemMIT OpenCourseWareNotes
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14. 14▶Lecture 3: Distributed Ledger as a Solution to an Information ProblemMIT OpenCourseWareNotes
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15. 15▶Lecture 6: Multilateral Trade Credit Set-offMIT OpenCourseWareNotes
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16. 16▶Lecture 6: Multilateral Trade Credit Set-offMIT OpenCourseWareNotes
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17. 17▶Lecture 11: Algorithmic Game TheoryMIT OpenCourseWareNotes
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18. 18▶Lecture 11: Algorithmic Game TheoryMIT OpenCourseWareNotes
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19. 19▶Lecture 1: Introduction to 14.129 Blockchain and Design of Financial SystemsMIT OpenCourseWareNotes
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20. 20▶Lecture 1: Introduction to 14.129 Blockchain and Design of Financial SystemsMIT OpenCourseWareNotes
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21. 21▶Lecture 9: Modern Encryption: Key ConceptsMIT OpenCourseWareNotes
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22. 22▶Lecture 9: Modern Encryption: Key ConceptsMIT OpenCourseWareNotes
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23. 23▶Lecture 2: Blockchain as a DatabaseMIT OpenCourseWareNotes
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24. 24▶Lecture 2: Blockchain as a DatabaseMIT OpenCourseWareNotes
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25. 25▶Lecture 5: Tokenized and Programmable AssetsMIT OpenCourseWareNotes
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26. 26▶Lecture 5: Tokenized and Programmable AssetsMIT OpenCourseWareNotes
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27. 27▶Talk: Modelling Multimodal Human Cognition with VLMs (Raquel Fernández)LxMLS Lisbon Machine Learning SchoolNotes
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28. 28▶Lecture 6: Vision and Language (Desmond Elliott / Bruno Martins)LxMLS Lisbon Machine Learning SchoolNotes
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29. 29▶Talk: Dynamic Sparse Attention at Scale (Marcos Treviso)LxMLS Lisbon Machine Learning SchoolNotes
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30. 30▶Lecture 5: Causality (Adèle Ribeiro)LxMLS Lisbon Machine Learning SchoolNotes
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31. 31▶Lecture 4: Transformers and Large Pretrained Models (André Martins)LxMLS Lisbon Machine Learning SchoolNotes
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32. 32▶Talk: The ladder of intelligence (Eric Xing)LxMLS Lisbon Machine Learning SchoolNotes
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33. 33▶Lecture 3: Introduction to Sequence Models (Noah Smith)LxMLS Lisbon Machine Learning SchoolNotes
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34. 34▶Talk: The Fiction Machine (Leon Bottou)LxMLS Lisbon Machine Learning SchoolNotes
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35. 35▶Lecture 2: Introduction to Deep Learning (Bhiksha Raj)LxMLS Lisbon Machine Learning SchoolNotes
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36. 36▶Optimizing the Full Stack for Generative Image and Video ModelsMIT OpenCourseWareNotes
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37. 37▶Optimizing the Full Stack for Generative Image and Video ModelsMIT OpenCourseWareNotes
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38. 38▶Lecture 4: The Capital Cost of Nuclear PowerMIT OpenCourseWareNotes
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39. 39▶Lecture 4: The Capital Cost of Nuclear PowerMIT OpenCourseWareNotes
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40. 40▶Lecture 12: Introduction to Radiation RiskMIT OpenCourseWareNotes
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41. 41▶Lecture 12: Introduction to Radiation RiskMIT OpenCourseWareNotes
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42. 42▶Lecture 1: Learning with Linear Models (Mário Figueiredo)LxMLS Lisbon Machine Learning SchoolNotes
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43. 43▶Lecture 10 - Constructing Training Target for Flow Models | Principles of Diffusion ModelsThe Principles of Diffusion ModelsNotes
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44. 44▶Lecture 9 - Introduction to Flow Models | Principles of Diffusion ModelsThe Principles of Diffusion ModelsNotes
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45. 45▶Lecture 8 - Diffusion Models: A Physical Intuition (SDE Framework) | Principles of Diffusion ModelsThe Principles of Diffusion ModelsNotes
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46. 46▶Lecture 7 - Noise Conditional Score Networks | Principles of Diffusion ModelsThe Principles of Diffusion ModelsNotes
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47. 47▶Lecture 6 - Denoising Score Matching | Principles of Diffusion ModelsThe Principles of Diffusion ModelsNotes
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48. 48▶Lecture 5 - Energy Based Models | Score Function | Principles of Diffusion ModelsThe Principles of Diffusion ModelsNotes
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49. 49▶Lecture 4 - Diffusion Models Practical | DDPM | Principles of Diffusion ModelsThe Principles of Diffusion ModelsNotes
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50. 50▶Lecture 3 - Introduction to Diffusion Models (DDPM) | Principles of Diffusion ModelsThe Principles of Diffusion ModelsNotes
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