Summary

This workshop is an introductory hands-on course on doing a machine learning project in Python. It is aimed at students and professionals who want to learn the basics of data preparation, classification, regression and model evaluation using the state-of-the-art machine learning library scikit-learn. Familiarity with Python will be helpful, but programming skills in any other programming language would do as well.

Syllabus

End-to-end machine learning project with real data
Data visualization
Feature subset selection
Classification & regression
Evaluate your model on test data

Instructor

Jure Žabkar is a researcher at AI Lab. He is currently an assistant professor at the University of Ljubljana and has over 10 years of professional experience in applied machine learning. He conducts research in machine learning and data mining, qualitative reasoning, cognitive robotics and systems for decision support. He has participated in EU projects ASPIC, XMEDIA and XPERO and several smaller industrial projects.

Attendee equipment prerequisites

We recommend a working installation of Python 3 and sci-kit library. Access to all the materials, code, and datasets will be provided to participants a couple of days before the workshop.

Predictive Modelling with Python