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.
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]
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.
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