Explore dimensionality reduction techniques in this 30-minute tutorial from the MIT Center for Brains, Minds, and Machines computational series. Delve into Principal Component Analysis (PCA), negentropy, and approximations, with a focus on their applications in brain and cognitive sciences. Learn through lecture slides, practical exercises, and discussions on current research problems. Access additional resources, including references and sign-up information for future tutorials, on the provided MIT Stellar platform. Benefit from the expertise of instructor Sam Norman-Haignere and engage in 'office hours' to work through exercises and address research challenges. Suitable for graduate students and postdocs with computational interests, this tutorial offers a comprehensive overview of dimensionality reduction methods and their relevance in cognitive science research.
Overview
Syllabus
Intro
Motivation
PCA
Negentropy
Approximations
Skew
Bottom Line
Sketch
Plot
Exercise
Taught by
MITCBMM