Machine Learning
Máster en Sistemas Inteligentes en Energía y Transporte
2025-10-02
About these notes
Course
- Syllabus year 25-26: SISTEMAS INTELIGENTES PARA EL PROCESADO DE DATOS Y AYUDA A LA DECISIÓN
- Campus Virtual 25-26
- The course is divided into two blocks: Machine Learning and Data Mining. All what follows is just about the Machine Learning part
Notes
- These notes are being continuously updated. Check you have the latest version
- These notes are intended as a script to the classes
- They do not definitely contain all the information given in the course and required in the exercises
- The code chunks are examples shown in class and the code is not particularly debugged
- Running the code without a careful read and thorough check is explicitly discouraged.
References
An introduction to statistical learning
James, Gareth and Witten, Daniela and Hastie, Trevor and Tibshirani, Robert
https://www.statlearning.com/The Elements of Statistical Learning
Hastie, Trevor and Tibshirani, Robert and Friedman, Jerome
https://web.stanford.edu/~hastie/ElemStatLearn/R for Data Science
Hadley Wickham and Garrett Grolemund
https://r4ds.had.co.nz/index.htmlApplied Machine Learning
Forsyth, David
https://courses.engr.illinois.edu/cs498aml/sp2019/