Round 1 - Introduction (15.04.2019 - 06.05.2019)In this round you will learn how to read in data from files or the internet. You will also learn how to visualize data using scatterplots.
Round 2 - Regression (22.04.2019 - 13.05.2019)In this round you will learn how to use machine learning for predicting a numeric quantity of interest (label) based on features of a data point.
Round 3 - Classification (29.04.2019 - 20.05.2019)In this round you will learn how to use machine learning for classifying data points according to different categories.
Round 4 - Model Validation and Selection (13.05.2019 - 27.05.2019) In this round you will learn how to evaluate (validate) the quality of a particular machine learning model or method.
Round 5 - Clustering (20.05.2019 - 03.06.2019) In this round you will learn how to use machine learning for organizing data points into coherent groups of similar data points.
Round 6 - Dimensionality Reduction (27.05.2019 - 10.06.2019) In this round you will learn how to use machine learning to compress vast amounts of raw data into a small number of features which contain most of the relevant information for the overall machine learning task.
