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Machine Learning I (Intro Lecture)

Difficulty level
Beginner
Speaker
Duration
33:58

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
Prerequisites

Experience with Python Programming Language.