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UofT -- Deep GenAI Course -- Summer25

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UofT GenAI Course -- Lecture 14: Maximum Likelihood Learning

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UofT GenAI Course -- Lecture 13: Explicit Distribution Learning - Sampling

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UofT GenAI Course -- Lecture 12: Naive Bayes -- Most Basic Generative Model

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UofT GenAI Course -- Lecture 11: Discriminative vs Generative Learning

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UofT GenAI Course -- Lecture 10: Generic Problem of Data Generation -- Basic Definitions

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UofT GenAI Course -- Lecture 9: Prompt Design for Task-specific Sampling from LLMs

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UofT GenAI Course -- Lecture 8: Statistical View on Fine-Tuning and LoRA

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UofT GenAI Course -- Lecture 7: Pre-training and Fine-tuning

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UofT GenAI Course -- Lecture 6: Examples of LLMs -- Size, Data and Practical Considerations

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UofT GenAI Course -- Lecture 4: Extracting Language Context by Self-Attention

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UofT GenAI Course -- Lecture 5: LMs -- Transformer-based LMs

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UofT GenAI Course -- Lecture 2: LMs -- Definition and Basic Bi-Gram Model

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UofT GenAI Course -- Lecture 3: Context-Aware LMs --Recurrent LMs

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UofT GenAI Course -- Lecture 1: LMs -- Tokenization and Embedding

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UofT GenAI Course -- Lecture 0: Course Overview and Logistics

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