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Getting ready
Course Information
Lectures
Lecture 1: Markov Models
Lecture 2: Applications of Markov Models and Text Preprocessing
Lecture 3: Introduction to Hidden Markov Models (HMMs)
Lecture 4: More HMMs
Lecture 5: Introduction to Recurrent Neural Networks (RNNs)
Lecture 6: Introduction to self-attention and transformers
Lecture 7: More transformers
Lecture 8: Applications of Large Language Models
Class demos
Recipe Generation using Transformers
Appendices
Baum-Welch (BW) algorithm
Attribution
Attributions
Index
