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