- Machine Learning: Introduction
- Linear Models, Optimization and SVMs (Notebook0)
- Other Machine Learning Models (Gaussian Classifier, NMC, kNN, RF) (Notebook1) (Notebook2)
- Neural Networks (Notebook3)
- Adversarial Machine Learning (Notebook4)
- Introduction to Numpy, Sklearn (Notebook1, Notebook2, Notebook3)
- Introduction to PyTorch (Notebook4, Notebook 5, Notebook6)
- Extra notebook on transfer learning Notebook 7