Spam filtering using various Supervised Learning models

An introductory session in supervised learning using several Machine Learning approaches from the scikit-learn library, to address the challenges of spam classification.

Who is this presentation for?
Beginning data scientists / machine learning engineers
Prerequisite knowledge:
Python
What you'll learn?
Participants will learn to apply several Supervised Learning models - Naive Bayes and ensemble methods - to the problem of spam classification, and compare the performance of the models.

Rick is a Learning Technology Manager for the School of Data Science at Udacity. He has worked in various education technology roles for the past 8 years, after serving as a public high school mathematics teacher and administrator for 24 years.