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1. 1▶LLMs | Tokenization Strategies | Lec 9Large Language ModelsNotes
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2. 2▶LLMs | Advanced Attention Mechanisms-II | Lec 8.2Large Language ModelsNotes
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3. 3▶LLMs | Advanced Attention Mechanisms-I | Lec 8.1Large Language ModelsNotes
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4. 4▶LLMs | Pre-training Strategies | ELMo & BERT | Lec 7Large Language ModelsNotes
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5. 5▶LLMs | Intro to Transformer: Positional Encoding and Layer Normalization | Lec 6.2Large Language ModelsNotes
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6. 6▶LLMs | Introduction to Transformer: Self & Multi-Head Attention | Lec 6.1Large Language ModelsNotes
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7. 7▶LLMs | Neural Language Models: Seq2Seq and Attention | Lec 5.3Large Language ModelsNotes
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8. 8▶LLMs | Neural Language Models: LSTM and GRU | Lec 5.2Large Language ModelsNotes
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9. 9▶LLMs | Neural Language Models: RNNs | Lec 5.1Large Language ModelsNotes
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10. 10▶LLMs | Word Representation: GloVe | Lec 4.2Large Language ModelsNotes
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11. 11▶LLMs | Word Representation: Word2Vec | Lec 4.1Large Language ModelsNotes
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12. 12▶LLMs | Language Models: Advanced Smoothing & Evaluation | Lec 3.2Large Language ModelsNotes
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13. 13▶LLMs | Introduction to Language Models| Lec 3.1Large Language ModelsNotes
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14. 14▶LLMs | Introduction to Natural Language Processing | Lec 02Large Language ModelsNotes
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15. 15▶LLMs | Introduction and Recent Advances | Lec 01Large Language ModelsNotes
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16. 16▶CSE101, Fall 22, Lec 12, part 1: Range search in balanced BSTsCSE101, Fall 2022, Introduction to Data Structures and AlgorithmsNotes
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17. 17▶CSE101, Fall 22, Lec 11: AVL treesCSE101, Fall 2022, Introduction to Data Structures and AlgorithmsNotes
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18. 18▶CSE101, Fall 22, Lec 10, Part 1: Tree traversalsCSE101, Fall 2022, Introduction to Data Structures and AlgorithmsNotes
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19. 19▶CSE101, Fall 22, Lec 10, Part 2: Self balancing trees and rotationsCSE101, Fall 2022, Introduction to Data Structures and AlgorithmsNotes
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20. 20▶CSE101, Fall 22: Lec 6, asymptotic running time analysis of quadratic time sorting algorithmsCSE101, Fall 2022, Introduction to Data Structures and AlgorithmsNotes
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21. 21▶CSE101, Fall 22, Lec 9: Binary Search TreesCSE101, Fall 2022, Introduction to Data Structures and AlgorithmsNotes
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22. 22▶CSE101, Fall 22, Lec 8: Binary heapsCSE101, Fall 2022, Introduction to Data Structures and AlgorithmsNotes
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23. 23▶CSE101, Fall 22, Lec 7, Part 1: Analysis of binary searchCSE101, Fall 2022, Introduction to Data Structures and AlgorithmsNotes
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24. 24▶CSE101, Fall 22, Lec 7, Part 2: An introduction to priority queues and binary heapsCSE101, Fall 2022, Introduction to Data Structures and AlgorithmsNotes
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25. 25▶CSE101, Fall 22, Lec 5: Starting asymptotic analysis of algorithms, big-Oh notationCSE101, Fall 2022, Introduction to Data Structures and AlgorithmsNotes
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26. 26▶CSE101, Fall 22, Lec 4: Stacks and recursionCSE101, Fall 2022, Introduction to Data Structures and AlgorithmsNotes
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27. 27▶CSE101 Fall 22, Lec 3, Part 3: An introduction to simulating recursion through stacksCSE101, Fall 2022, Introduction to Data Structures and AlgorithmsNotes
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28. 28▶CSE101 Fall 22, Lec 3, Part 2: An introduction to stacks and parentheses checkingCSE101, Fall 2022, Introduction to Data Structures and AlgorithmsNotes
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29. 29▶CSE101 Fall 22, Lec 3, Part 1: Reversing a linked listCSE101, Fall 2022, Introduction to Data Structures and AlgorithmsNotes
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30. 30▶CSE101, Fall 22: Linked listsCSE101, Fall 2022, Introduction to Data Structures and AlgorithmsNotes
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31. 31▶CSE204, Lec 19: Basic of cryptography, from a complexity perspectiveCSE204, Spring 2022: Computational Complexity TheoryNotes
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32. 32▶CSE204, Lec 17: Proving the Sumcheck protocol for #SAT, a short discussion about MIPCSE204, Spring 2022: Computational Complexity TheoryNotes
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33. 33▶CSE204, Lec 18: The PCP theorem and hardness of approximationCSE204, Spring 2022: Computational Complexity TheoryNotes
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34. 34▶CSE204, Lec 16: Proving the set lower bound protocol, and starting the proof that IP = PSPACECSE204, Spring 2022: Computational Complexity TheoryNotes
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35. 35▶CSE204, Lec 15: Arthur-Merlin protocols and the Goldwasser-Sipser set lower bound protocolCSE204, Spring 2022: Computational Complexity TheoryNotes
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36. 36▶CSE204, Lec 13: Relating BPP to other complexity classesCSE204, Spring 2022: Computational Complexity TheoryNotes
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37. 37▶CSE2014, Lec 12: Introduction to randomized complexity classes and BPPCSE204, Spring 2022: Computational Complexity TheoryNotes
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38. 38▶CSE204, Lec 14: Introduction to Interactive ProtocolsCSE204, Spring 2022: Computational Complexity TheoryNotes
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39. 39▶CSE 204, Lec 10, Part 1: Complete languages for the polynomial hierarchyCSE204, Spring 2022: Computational Complexity TheoryNotes
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40. 40▶CSE204, Lec 10, Part 2: Introduction to circuit complexityCSE204, Spring 2022: Computational Complexity TheoryNotes
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41. 41▶CSE204, Lec 9: Equivalences of definitions of the polynomial hierarchyCSE204, Spring 2022: Computational Complexity TheoryNotes
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42. 42▶CSE204, Lec 3: 3SAT is NP-complete, and the class co-NPCSE204, Spring 2022: Computational Complexity TheoryNotes
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43. 43▶CSE204, Lec 2: NP-completeness and the Cook-Levin TheoremCSE204, Spring 2022: Computational Complexity TheoryNotes
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44. 44▶CSE201, Lec 15: Karatsuba multiplication and Strassen's matrix multiplicationCSE201, Winter 2022: Analysis of AlgorithmsNotes
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45. 45▶CSE201, Lec 14: Linear time selection using divide and conquerCSE201, Winter 2022: Analysis of AlgorithmsNotes
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46. 46▶CSE201, Lec 13: Introduction to divide and conquer, Mergesort and the stock market problemCSE201, Winter 2022: Analysis of AlgorithmsNotes
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47. 47▶CSE201, Lec 12: Dijkstra's algorithms, All Pairs Shortest Paths, and matrix multiplicationCSE201, Winter 2022: Analysis of AlgorithmsNotes
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48. 48▶CSE201, Lec 11: Single source shortest paths and the Bellman-Ford algorithmCSE201, Winter 2022: Analysis of AlgorithmsNotes
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49. 49▶CSE201, Lec 10: Minimum Spanning TreesCSE201, Winter 2022: Analysis of AlgorithmsNotes
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50. 50▶CSE201, Lec 9: Huffman codingCSE201, Winter 2022: Analysis of AlgorithmsNotes
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