Machine learning has become an indispensable tool across many areas of research and commercial applications. From text-to-speech for your phone to detecting the Higgs-Boson particle, machine learning excels at extracting knowledge from large amounts of data. This talk gives a general introduction to machine learning and introduces practical tools for you to apply machine learning in your research. It focuses on one particularly important subfield of machine learning: supervised learning. The goal of supervised learning is to “learn” a function that maps inputs x to an output y, by using a collection of training data consisting of input-output pairs. The video walks through the formalizing of a problem as a supervised machine learning problem, the creation of the necessary training data and the application and evaluation of a machine learning algorithm. The talk should give you all the necessary background to start using machine learning yourself.