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EVRI-thing You Need to Know About t-SNE & UMAP in PLS_Toolbox/Solo

January 6, 2022


Our webinar series continues on Thursday, January 6 with “EVRI-thing You Need to Know About t-SNE & UMAP in PLS_Toolbox/Solo.” EVRI President Barry M. Wise will present with help from Senior Data Scientist Manuel A. Palacios.

PLS_Toolbox and Solo version 9.0 include two relatively new data visualization methods, t-distributed Stochastic Neighbor Embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP). These routines, from the scikitlearn library for Python, can now be found in our interfaces (and for PLS_Toolbox, also at the MATLAB® command line). We will introduce these methods and show how to access them in the new PLS_Toolbox and Solo. In this webinar we’ll cover

  • Basic ideas behind t-SNE and UMAP
  • How to access t-SNE and UMAP in the Analysis Interface
  • Important meta-parameters in the methods
  • Examples on chemical/spectroscopic data sets
  • Comparison to Principal Components Analysis (PCA)

A question and answer session will follow the webinar. Don’t miss your chance to quiz Barry, Manny and the Eigen-Guys about how to use t-SNE and UMAP in PLS_Toolbox and Solo version 9.0!

Register for “EVRI-thing You Need to Know About t-SNE and UMAP in PLS_Toolbox/Solo” through your existing Eigenvector account, or create one. The webinar is free, but you must register to attend. Find the webinar near the bottom of the page under the “Purchase” tab.

The webinar will be live on Thursday, January 6 at 7:00am PDT, (that’s 16:00 CET, 10:00 EST). Reserve your seat today and we’ll send you a WebEx meeting invitation a couple days before the event. We hope you can attend, but if you sign up and can’t make it, we’ll send you a link to view the recording the day after the webinar.

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