Applied Machine Learning for Audio Classification

Abstract: Ale Koretzky, Head of Machine Learning at Splice.com and creator of tuneSplit, will discuss and compare approaches and techniques for Audio Classification; from simple Nearest Neighbor methods like k-NN, to Decision Trees to Convolutional Neural Networks (CNN) and Deep Autoencoders. Using examples with real data, Koretzky will address the importance of both Feature Engineering and Feature Learning and how they can work together. At the end of the session, students should be able to implement most of the techniques but more importantly, develop the key intuitions behind Audio Classification in order to address any related problem with domain-specific data.