Statistical-Learning-Review

This is a review of the theory and application of different Statistical Learning mpdels for Classification, Regression and Clustering. To each topic there is a dedicated folder which contains book chapter from the book "An Introduction to Statistical Learning with Applications in R - Gareth James, Daniela Witten, Trevor Hastie Robert Tibshirani - Springer Texts in Statistics - Series Editors: G. Casella S. Fienberg I. Olkin" and jupyter-noteboks which illustrate practical applications using Scikit-Learn. The materials includes also sources (slides for theory and codes for practical applications) that I collected from Data Science classes I participated at the University of Illinois at Chicago as well as online course of Machine Learning, Deep Learning and Computer Vision I followed in Udemy and Udacity