Dimensionality Reduction I (Intro Lecture)
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.
- 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.