Solving all of the conceptual and applied problems in the popular textbook Introduction to Statistical Learning with Python.
The project will cover:
- Linear regression
- Classification
- Resampling & Cross-validation
- Linear model selection and regularisation
- Non-linear modelling
- Tree-based methods
- Support vector machines
- Deep learning
- Survival analysis
- Unsupervised learning
- Multiple hypothesis testing