課程連結: https://web.stanford.edu/class/cs224n/
This repository contains solutions to programming assignments for CS224N: Natural Language Processing with Deep Learning course offered by Stanford University in Winter 2024. The assignments cover a range of topics in natural language processing (NLP) and deep learning.
- Assignment 1: Word Vectors
- Introduction to word vectors and various models.
- Assignment 2: Backpropagation, Neural Networks, Dependency Parsing
- Implementation of backpropagation, neural networks, and dependency parsing.
- Assignment 3: RNNs, Language Models, Vanishing/Exploding Gradients
- Utilization of recurrent neural networks (RNNs), language modeling, and handling vanishing/exploding gradients.
- Assignment 4: Machine Translation, Attention Mechanism, Subword Models
- Development of machine translation models incorporating attention mechanisms and subword modeling.
- Assignment 5: Transformers
- Exploration and implementation of transformer models for various NLP tasks.
- /a1: Contains code and relevant files for Assignment 1 (Word Vectors).
- /a2: Contains code and relevant files for Assignment 2 (Backpropagation, Neural Networks, Dependency Parsing).
- /a3: Contains code and relevant files for Assignment 3 (RNNs, Language Models, Vanishing/Exploding Gradients).
- /a4: Placeholder for Assignment 4 (Machine Translation, Attention Mechanism, Subword Models).
- /a5: Placeholder for Assignment 5 (Transformers).
To explore the solutions and code for completed assignments, navigate to the respective folders (a1, a2, a3). For incomplete assignments (a4, a5), stay tuned for updates.
- Python 3.x
- PyTorch
- NumPy
- Matplotlib
- NLTK