Stats 3 — Lecture 11: Supervised Machine Learning
Channel: Jonas Obleser
Date: 16/01/2023

Main topics today:
-- Basic ideas of supervised learning, with focus on logistic regression revisited and classification
-- Classification: signal detection basics;  cross-validation
-- Other classifier examples: Naive Bayes, Support Vector Machine
-- Outlook: The big picture of supervised learning, with very (!) brief glimpse at Autoencoders and Transformers
Slides are here: https://www.dropbox.com/s/n0tha5bfzjj5df4/Stats%203%20VL11.pdf?dl=1

(sorry for the slide window being slightly cropped off in the image)

NOTE: Lecture 10 in the series (on SEM continued; factor analysis) is missing due to a technical error. Please see my SEM/FA videos 9--1 in the older lecture series “Multivariate Statistik” instead.