The main reading material will consist of lecture slides and related materials, which will be distributed at the beginning of the course. Optional further reading is also recommended from the following textbooks
- Hastie, T., Tibshirani, R. and Friedman, J., The Elements of Statistical Learning: Data Mining, Inference and Prediction. 2nd Edition, Springer, 2009.
- K. Murphy, Machine Learning: A Probabilistic Perspective, MIT Press, 2012.
- C. M. Bishop, Pattern Recognition and Machine Learning, Springer 2006.
*A more detailed reading list will be supplied prior to the start of the programme
**Course content, faculty and dates may be subject to change without prior notice