This repo outlines our submissions for the four tasks of the course "Advanced Machine Learning" at ETH Zurich during the academic year 2019-2020. Each folder contains the code (Jupyter notebook for each task) as well as a short README file describing the assignment. More information about the tasks and our approaches can be found at the PDF report "Advanced_Machine_Learning_Report.pdf".

"Machine learning algorithms are data analysis methods which search data sets for patterns and characteristic structures. Typical tasks are the classification of data, automatic regression and unsupervised model fitting. Machine learning has emerged mainly from computer science and artificial intelligence, and draws on methods from a variety of related subjects including statistics, applied mathematics and more specialized fields, such as pattern recognition and neural computation. Applications are, for example, image and speech analysis, medical imaging, bioinformatics and exploratory data analysis in natural science and engineering." [AML_ETH]

This repo contains mainly Jupyter notebook files which can be run after installing Jupyter Notebook. Run the following command at the Terminal (Mac/Linux) or Command Prompt (Windows):

pip install notebook