CUrriculum

Monday - Classes from 9:30 to 17:30

 

Session 1: Introduction to basic concepts using linear regression

Session 2: Classification. Naive Bayes. Performance metrics

 

 

Tuesday - Classes from 9:30 to 17:30

 

Session 3: Decision trees and random forests

Session 4: Logistic regression and generalized linear models

 

 

Wednesday - Classes from 9:30 to 17:30

 

Session 5: Support vector machines: Basics

Session 6: Support vector machines: simple kernels and solvers


 

 

Thursday - Classes from 9:30 to 17:30

 

Session 7: Basic elements of learning theory

Session 8: Neural networks and algorithmic differentiation

 

 

Friday - Classes from 9:30 to 17:30

 

 Session 9: Tricks of the trade for training neural networks

Session 10: Convolutional and recurrent neural networks