Machine Learning

Syllabus, evaluation and other information:

• Syllabus, evaluation and other information.

Some usefull references:

• Hastie, Tibshirani, Friedman - Elements of Statistical Learning.

Presentations:

• Statistical and Machine Learning
• Linear Regression
• Collinearity
• Ridge Regression
• Cross Validation
• Maximum Likelihood with Restrictions
• B-Splines
• EM algorithm, Gaussian mixture and k-means

Codes:

Codes and data for the course are available at the github repository: https://github.com/IrvingGomez/MachineLearning