Traditional Statistics vs Machine Learning

#datascience #statistics #machinelearning #ai What is the difference between machine learning (ML) and traditional statistics? How did they historically develop? And is artificial intelligence (AI) something else? When can I use which? And how should I go about learning these methods, for example if I want to become a data scientist? These are some of the questions that Ben Geisler poses to Professors Ulrich Mansmann and Ludwig Christian Hinske of LMU’s IBE. 0:25 Differences between ML, traditional statistics and AI 4:24 Differences between deep learning and ML? 5:20 Reinforcement learning 6:34 Are there instances where ML/AI/deep learning should not be used? 7:44 Explainable AI/ML 11:06 When is ML/AI/deep learning most useful? 13:21 I have very little data - can I use ML? 16:33 Degree program vs MOOC References: -L. Breiman: Statistical Modeling: The Two Cultures. Statistical Scince 2021 https://bit.ly/35bnBcT -E. Christodoulou et al.: A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models. J Clin Epidemiol 2019 https://bit.ly/3HGJyhb