PAPIs Latam 2019

In this talk, we will analyze some theoretical aspects related to the results of an A/B test, in scenarios where Machine Learning models are involved. We will discuss the risks of taking results of an A/B test, or other purely comparative methodology, as a prediction of future gains. We will review the main practical and theoretical differences between A/B test and forecasting, when conducting ML related projects. This discussion targets a mixed audience, embracing people from technical and business areas. Also, it will be illustrated with real world examples taken from actual A/B tests.