Episode #20: Building Interpretable Machine Learning Models with Christoph Molnar DataHack Radio

How do we build interpretable machine learning models? Or, in other words, how do we build trust in the models we design? This is such a critical question in every machine learning project. We need to find a way to use these powerful ML algorithms and still make them work in business setting. So in this episode #20 of our DataHack Radio podcast, we welcome Christoph Molar, author of the popular book - "Interpretable Machine Learning". Who better to talk about this fundamental and critical topic? Read more here: https://www.analyticsvidhya.com/blog/2019/03/datahack-radio-interpretable-machine-learning-christoph-molnar