Unsupervised machine learning with Python

We will explore different unsupervised learning algorithms for tasks such as clustering, dimensionality reduction and anomaly detection using scikit-learn. We will gain hands-on experience on how to utilize them in different scenarios.

Agenda

19:00 - 19:10 Welcome and Community announcements

19:10 - 19:25 Short intro to Pythonic Startups at the Centre for Entrepreneurship

19:25 - 19:40 Preparation for the hands on and networking

19:40 - 21:10 Hands-on (bring your laptops)

21:10 - 21:30 Q&A, networking continued

About the speaker:
Kiril Ralinovsky is a cofounder and Lead Data Scientist at onwrks. Before that he researched distributed anomaly detection in the context of an Industry 4.0 project.

Setup for hands-on:

• Python 3

• pandas >=[masked]

• sklearn >=[masked]

• numpy >=[masked]

Gender policy 

We want to make sure that we have at least 50% female attendees, so we ask our non female attendees to come with a female plus one.