This repo contains the models used in the project part of the ETH course Advanced Machine Learning by Prof. Joachim M. Buhmann and Dr. Carlos Cotrini, taken in the fall semester 2021 (252-0535-00L). The goal of the course was to learn about advanced ML techniques like structured SVMs, Ensemble Methods, Deep Learning or non-parametric Bayesian methods and to get hands-on experience in three different projects. The projects were graded in a competitive manner. I ranked Top 10 out of over 200 Teams in all three competitions.
You need Python and Jupyter to run the files.
Just clone this repo with
git clone https://github.com/MrBirrd/ETH_AdvancedMachineLearning.git
Then go to the folder and install the requirements.
cd ETH_AdvancedMachineLearning
python -m pip install -r requirements.txt
Each project has its own folder with a Jupyter Notebook which shows the data processing, the model and evaluation. There are additional files if necessary. Please note that the original dataset cannot be provided in some cases due to privacy reasons.