Prof. Dr. Nilesh Madhu from Gent University contributes to our IKS event series with an online lecture entitled: „Machine Learning for Audio“ Incorporating a priori knowledge increases the performance of audio processing algorithms. Classical, knowledge‐based approaches depended on hand‐engineered features and painstaking statistical models for this. In recent years these have been increasingly superseded by data‐based approaches using (deep) neural networks (DNNs). In this talk Prof. Madhu will contrast knowledge‐based and data‐based approaches for different applications and also discuss some pertinent questions in relation to the use of DNNs such as: How can we allow DNNs to generalize better, and what are some pitfalls? These shall be illustrated on specific applications. The overall aim of the talk is to present a general (qualitative) appreciation of the two classes of approaches. Perhaps this will stimulate work on how to obtain the “best of both worlds“.