Exploring Dimensionality Reduction From Several Angles
Let's dive into the details surrounding Dimensionality Reduction From Several Angles.
- Why would we want to reduce the number of features ? And how do we do it ?
- UMAP is one of the most popular
- Brilliant 20% off: http://brilliant.org/DeepFindr/ ▭▭ Papers / Resources ▭▭▭ Intro to Dim.
- Contents: Motivation 1 - Data Compression, Motivation 2 - Visualization, Principal Component Analysis - Problem Formulation, ...
- Papers / Resources ▭▭▭ Colab Notebook: ...
In-Depth Information on Dimensionality Reduction From Several Angles
Tamara Munzner, Professor, Department of Computer Science, University of British Columbia Presents... This video is part of the Udacity course "Introduction to Computer Vision". Watch the full course at ... A very general overview of Fit for purpose data store for AI workloads → https://ibm.biz/BdmLTX Discover how Principal Component Analysis (
This video contains the basic concepts of
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