Machine-Learning-Portfolio

This portfolio is being developed by Gabriel Estivalet to use Machine Learning techniques on regression and classification problems. The files that start with Udacity are projects developed following course content from the School

The sources used as guidelines for these projects are:

• General Assembly: Data Science course materials;

• Udacity Nanodegree materials;

• Muller & Guido: Introduction to Machine Learning with Python, O'Reilly, 2016;

• Wes McKinney: Python for Data Analysis, O'Reilly, 2013;

• Allen B. Downey: Think Stats, O'Reilly, 2015.