Data Science with Python, Part 1

Monday, February 24, 2020
2:45 pm–4:15 pm
Alexander Library


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. 

Held in Alexander Library, 4th floor, JetStream Room, Room No: 404  (Instructor, Sanket Badhe)

RSVP for any/all of the Python workshops

Alexander Library