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  1. [Fall 2023] Speech Recognition and Understanding (Lecture2: Introduction of Speech Recognition)Fall2023-SpeechRecognition&UnderstandingNotes
  2. [Fall 2023] Speech Recognition and Understanding (Lecture 4: Feature extraction)Fall2023-SpeechRecognition&UnderstandingNotes
  3. [Fall 2023] Speech Recognition and Understanding (Lecture 5: Alignments)Fall2023-SpeechRecognition&UnderstandingNotes
  4. [Fall 2023] Speech Recognition and Understanding (Lecture 9: Hidden Markov Models part III)Fall2023-SpeechRecognition&UnderstandingNotes
  5. [Fall 2023] Speech Recognition and Understanding (Lecture 10: Forward-backward algorithm for CTC)Fall2023-SpeechRecognition&UnderstandingNotes
  6. [Fall 2023] Speech Recognition and Understanding (Lecture 13: Search)Fall2023-SpeechRecognition&UnderstandingNotes
  7. [Fall 2023] Speech Recognition and Understanding (Lecture 22: Advanced topics on end-to-end ASR II)Fall2023-SpeechRecognition&UnderstandingNotes
  8. [Fall 2023] Speech Recognition and Understanding (Lecture 3: Speech Recognition Formulation)Fall2023-SpeechRecognition&UnderstandingNotes
  9. [Fall 2023] Speech Recognition and Understanding (Lecture 7: Hidden Markov Models)Fall2023-SpeechRecognition&UnderstandingNotes
  10. [Fall 2023] Speech Recognition and Understanding (Lecture 8: Hidden Markov Models part II)Fall2023-SpeechRecognition&UnderstandingNotes
  11. POS Tagging; Named Entity Recognition; Hidden Markov ModelNatural Language Processing (Spring 2024)Notes
  12. Hidden Markov Model: Parameter Estimation & Efficient InferenceNatural Language Processing (Spring 2024)Notes
  13. Midterm overviewNatural Language Processing (Spring 2024)Notes
  14. “Taskification” and Valid BenchmarksNatural Language Processing (Spring 2024)Notes
  15. Finetuning a seq2seq model in 🤗 (demo); RLHFNatural Language Processing (Spring 2024)Notes
  16. Finetuning DeBERTa in 🤗 (demo); Instruction FTNatural Language Processing (Spring 2024)Notes
  17. Transformer (Decoder); Pretraining & FinetuningNatural Language Processing (Spring 2024)Notes
  18. Attention; Transformer (Encoder)Natural Language Processing (Spring 2024)Notes
  19. Neural machine translationNatural Language Processing (Spring 2024)Notes
  20. Language modelingNatural Language Processing (Spring 2024)Notes
  21. Fall2022-SpeechRecognition&Understanding (Lecture16 - Neural Networks for Acoustic Modeling)Fall2022-SpeechRecognition&UnderstandingNotes
  22. Fall2022-SpeechRecognition&Understanding (Lecture17 - Neural Network Language Modell)Fall2022-SpeechRecognition&UnderstandingNotes
  23. Fall2022-SpeechRecognition&Understanding (Lecture13 - N-gram Language Model)Fall2022-SpeechRecognition&UnderstandingNotes
  24. Fall2022-SpeechRecognition&Understanding (Lecture14 - Intro to Deep Learning for Speech Recognition)Fall2022-SpeechRecognition&UnderstandingNotes
  25. Fall2022-SpeechRecognition&Understanding (Lecture12 - Advanced Acoustic Modeling)Fall2022-SpeechRecognition&UnderstandingNotes
  26. Fall2022-SpeechRecognition&Understanding (Lecture8 - Alignment Paths)Fall2022-SpeechRecognition&UnderstandingNotes
  27. Fall2022-SpeechRecognition&Understanding (Lecture11 - Hidden Markov Model III)Fall2022-SpeechRecognition&UnderstandingNotes
  28. Fall2022-SpeechRecognition&Understanding (Lecture10 - Hidden Markov Model II)Fall2022-SpeechRecognition&UnderstandingNotes
  29. Fall2022-SpeechRecognition&Understanding (Lecture9 - Hidden Markov Models I)Fall2022-SpeechRecognition&UnderstandingNotes
  30. Fall2022-SpeechRecognition&Understanding (Lecture7 - ESPnet tutorial2 (New Task))Fall2022-SpeechRecognition&UnderstandingNotes
  31. MIT CompBio Lecture 03 - Hashing BLAST Database Search (Fall'19)Machine Learning in Genomics - Fall 2019Notes
  32. MIT CompBio Lecture 15 - eQTLs Mediation (Fall 2019)Machine Learning in Genomics - Fall 2019Notes
  33. MIT CompBio Lecture 14 - GWAS (Fall 2019)Machine Learning in Genomics - Fall 2019Notes
  34. MIT Compbio Lecture 13 - Population Genetics (Fall 2019)Machine Learning in Genomics - Fall 2019Notes
  35. MIT Compbio Lecture 12 - Deep Learning (Fall '19)Machine Learning in Genomics - Fall 2019Notes
  36. MIT CompBio Lecture 11 - Network inference and analysis (Fall '19)Machine Learning in Genomics - Fall 2019Notes
  37. MIT CompBio Lecture 10 - Regulatory Genomics (Fall '19)Machine Learning in Genomics - Fall 2019Notes
  38. MIT CompBio Lecture 09 - Epigenomics II (Fall '19)Machine Learning in Genomics - Fall 2019Notes
  39. MIT CompBio Lecture 08 - Epigenomics I (Fall '19)Machine Learning in Genomics - Fall 2019Notes
  40. MIT CompBio Lecture 07 - RNA world, RNA-seq, RNA folding (Fall '19)Machine Learning in Genomics - Fall 2019Notes
  41. Lecture 1 - IntroductionCSE549 - Computational Biology - 2010 SBUNotes
  42. Lecture 14 - Markov ModelsCSE549 - Computational Biology - 2010 SBUNotes
  43. Lecture 15 - Hidden Markov ModelsCSE549 - Computational Biology - 2010 SBUNotes
  44. Lecture 11 - Smith-Waterman AlgorithmCSE549 - Computational Biology - 2010 SBUNotes
  45. Lecture 12 - Space-Efficient Dynamic ProgrammingCSE549 - Computational Biology - 2010 SBUNotes
  46. Lecture 9 - Projects & Approximate String MatchingCSE549 - Computational Biology - 2010 SBUNotes
  47. Lecture 13 - Introduction to Gene FindingCSE549 - Computational Biology - 2010 SBUNotes
  48. Lecture 8 - String Matching AlgorithmsCSE549 - Computational Biology - 2010 SBUNotes
  49. Lecture 10 - Dynamic ProgrammingCSE549 - Computational Biology - 2010 SBUNotes
  50. Lecture 7 - Suffix Arrays and AssemblyCSE549 - Computational Biology - 2010 SBUNotes

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