Skip to main content

Machine Learning I (Intro Lecture)

Difficulty level

This lecture is part of the Neuromatch Academy (NMA), a massive, interactive online summer school held in 2020 that provided participants with experiences spanning from hands-on modeling experience to meta-science interpretation skills across just about everything that could reasonably be included in the label "computational neuroscience". 


This lecture provides an overview of generalized linear models (GLM) and contains links to 2 tutorials, lecture/tutorial slides, suggested reading list, and 3 recorded question and answer sessions.

Topics covered in this lesson
  • Overview of generalized linear models for different types of output and different likelihoods
  • Classifiers and regularizers
  • Review of maximum likelihood estimation for the parameters and issues around overfitting and regularization

Experience with Python Programming Language.