Data Science with Python, Part 1

Friday, November 15, 2019
1 pm–3 pm
Alexander Library

Contact:

Ryan Womack

This workshop delves into a wider variety of basic supervised learning methods for both classification and regression (Linear Regression, Logistic Regression, Naive Bayes, k-Nearest Neighbor). In the last part, we will discuss unsupervised learning techniques namely k-Means, PCA. We will apply all techniques on a dataset and compare each of these techniques in terms of accuracy, inference, etc.

Alexander Library, Room 415

Instructor: Sanket Badhe

Alexander Library