Lecture

Data Characterization: PCA & Spike Sorting

In course

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Description

This lecture covers the concept of Principal Component Analysis (PCA) in data processing, focusing on reducing variables to simplify data interpretation. It also delves into Spike Sorting, a method to identify distinct shapes in recorded data, using PCA to reduce complexity and analyze characteristics. The instructor explains how PCA transforms data into uncorrelated elements and the importance of eigenvalues in reducing problem dimensions.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_9y8evf5u

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Ontological neighbourhood

Information engineering

Data science: Topics in data science

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