Spring 2024 | Lecture 1 - Intro and Word2vec
Spring 2024 | Lecture 2 - Word Vectors and Language Models
Spring 2024 | Lecture 3 - Backpropagation, Neural Network
Spring 2024 | Lecture 4 - Dependency Parsing
Spring 2024 | Lecture 5 - Recurrent Neural Networks
Spring 2024 | Lecture 6 - Sequence to Sequence Models
Spring 2024 | Lecture 7 - Attention, Final Projects and LLM Intro
2023 | Lecture 8 - Self-Attention and Transformers
2023 | Lecture 9 - Pretraining [DGfCRXuNA2w]_output
Spring 2024 | Lecture 10 - Post-training by Archit Sharma
Spring 2024 | Lecture 11 - Benchmarking by Yann Dubois
Spring 2024 | Lecture 12 - Efficient Training, Shikhar Murty
Spring 2024 | Lecture 13 - Brain-Computer Interfaces, Chaofei Fan
Spring 2024 | Lecture 14 - Reasoning and Agents by Shikhar Murty
Spring 2024 | Lecture 15 - After DPO by Nathan Lambert
Spring 2024 | Lecture 16 - ConvNets and TreeRNNs
2023 | Lecture 11 - Natural Language Generation
Lecture 18 - NLP, Linguistics, Philosophy
2023 | Lec. 19 - Model Interpretability & Editing, Been Kim
2023 | Lecture 16 - Multimodal Deep Learning, Douwe Kiela
2023 | PyTorch Tutorial, Drew Kaul
2023 | Python Tutorial, Manasi Sharma
2023 | Hugging Face Tutorial, Eric Frankel