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Dimensionality Reduction 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 introduces the core concepts of dimensionality reduction.

Topics covered in this lesson
  • Introduction to core concepts of dimensionality reduction applied to multi-dimensional neural recordings
  • Geometric view of data
  • Principal component analysis
  • Dimensionality reduction and reconstruction
  • Nonlinear dimensionality reduction
  • Rationale for the  dimensionality reduction approach
  • Geometric perspective to dimensionality reduction

Experience with Python Programming Language.

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