Natural Language Processing
Spring 2024 (Jan–Apr) · Mahindra University
Spring 2024Course CS3126ELT 1
| Week | Topic | Resources |
|---|---|---|
| Week 1 | Introduction to NLP and its applications | |
| Week 2 | Regular Expressions, Text Normalization |
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| Week 3 | Text pre-processing (Stop Words, Bag-of-Words, TF-IDF, POS Tagging, NER) |
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| Week 4 | Distributional semantics, Vector Embeddings |
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| Week 5 | Language Models-Probabilistic Language Modeling |
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| Week 6 | Neural Networks and Neural Language Modeling | Lecture SlidesNeural Networks and Neural Language Models (Textbook Chapter)PyTorch Hands-on TutorialsNeural Networks, Backpropagation [Notes-CS224n]
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| Week 7 | Recurrent Neural Networks, LSTM | Lecture SlidesRNN SlidesRNNs and LSTMs (Textbook Chapter)Language Models, RNN and LSTM [CS224n Lecture Notes]RNN PyTorch Slides & ImplementationOn the difficulty of training Recurrent Neural Networks [Research Paper][Additional]Vanishing and Exploding gradients (Colab Notebook)
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| Week 8 | Advanced topics - Encoder Decoder Models, Attention |
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| Week 9 | Advanced topics - Multi-head attention, Transformers |
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| Week 10 | Advanced topics - BLEU Score, Introduction to LLM's Pretraining, Fine-tuning | Lecture SlidesThe Illustrated Transformer by Jay AlammarAttention is all you Need [Research Paper]Attention Visualization
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| Week 11 | Advanced topics - MLM, BERT and NLP Applications | Lecture SlidesThe Illustrated BERT, ELMo, and co. by Jay AlammarBERT [Research Paper]Hugging Face - BERT
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