VU Hands on Machine Learning

Abstract

This course is the practical/experimental companion to Clemens Apprich's seminar on the theory and history of Machine Learning. While it is not a formal requirement to also attend this other course, we highly recommend to jointly attend both of those two courses. Ongoing course documentation: https://tantemalkah.at/2023/machine-learning/

Description

The course features three major parts we will focus on: 1. Intro & linear regression models: in the first weeks of the course we will familiarise ourselves with the basic setup and the scripting basics we need to create and experiment with simple linear regression models with Python on your own computing device. 2. Recommender systems: after we gained some familiarity with creating and working on linear regression models, we focus on recommender systems and creating and experimenting with machine learning models that can be used in recommender systems 3. Project work & open experimentation: the final weeks of the course aim at defining specific (prototype) projects, which the attendees will work on either individually or in groups, as part of their final exercise in this course

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