09:00 - 17:00
Kopernikus 2 WS
ML Intro Day
Machine learning is often hyped, but how does it work? In this workshop, Dr. Pieter Buteneers will show you hands-on how you can build your own machine learning models. We will cover basic machine learning concepts such as regression, classification, over-fitting, cross-validation, and many more. After the workshop, you will go home with the basics of machine learning so you can start off on your own projects.
Inhalt & Ablauf
- The basics of Jupyter notebooks and processing data in Python
- The basic concepts of linear regression
- Non-linear regression
- Time series prediction
- Recommender systems
- Anomaly detection
The goal of each exercise is to learn the basic concepts behind the topics above. Most of the code will be provided for you so this is not a coding exercise. So if you don’t have a Python background this won’t be an issue. You will only need to implement the essential parts of the code to really understand the concepts. Typically this is just around 5 lines of code per exercise.
At the beginning of each exercise I will introduce you to the task at hand and explain what we are trying to accomplish. During the exercise I will answer all the questions you might have so you don’t need to be stuck on silly coding mistakes. And once the majority of people have finished the exercise I will go over the solutions and I will provide a bit more context to how to apply this in real life tasks.
Zielgruppe & Anforderungen
Anybody who can write some code in whatever programming language should be able to follow the workshop. We make use of an iPython/Jupyter Notebook running on a dedicated server, so nothing but a laptop with an internet connection is required to participate.