Completed During The Fall'22 & Spring'23 at Stanford School of Engineering.
CS221 - Artificial Intelligence Principles and Techniques
- Search (See Project)
- Constraint satisfaction problems (See Project)
- Markov decision processes (See Project)
- Planning and game playing (See Project)
- Machine learning (See Project)
- Bayesian networks (See Project)
- Graphical models (See Project)
- Logic (See Project)
CS224N - Natural Language Processing with Deep Learning
- Word vectors (See Project 1; See Project 2)
- Neural Networks (See Project)
- Dependency Parsing (See Project)
- RNNs and Language Models (See Project)
- Neural Machine Translation and Attention (See Project)
- Transformers and Pretraining (See Project)
- Using PyTorch from scratch
CS224U - Natural Language Understanding
- Vector-space models
- Sentiment analysis
- Contextual representations
- Grounding
- Natural language inference
- Information retrieval
- Relation extraction