Google open sources Embedding Projector to make high-dimensional data more manageable

Dear friends,  I’m sharing this great news that Google opens Embedding Projector for the world. Now everyone could enjoy the convenient approach to visualize high dimensional data on the web browser.

Based on my personal programming experience, t-SNE is a great method for high-dimensional data visualization, better than PCA on some data sets like MNIST.

You can download the Matlab Toolbox for Dimensionality Reduction; or download the t-SNE method for different platforms: t-SNE codes.

Moreover, check the following papers if you want to learn more  details about dimensionality reduction.

  • L.J.P. van der Maaten and G.E. Hinton. Visualizing High-Dimensional Data Using t-SNE. Journal of Machine Learning Research 9(Nov):2579-2605, 2008. PDF [Supplemental material] [Talk]
  • L.J.P. van der Maaten, E.O. Postma, and H.J. van den Herik. Dimensionality Reduction: A Comparative Review. Tilburg University Technical Report, TiCC-TR 2009-005, 2009. PDF

Here are the links for more information:

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Plan: Introduce the Softwares for Machine Learning

    Software List:  Matlab Basic Matlab  Advanced: LMS  Softmax SVM Neural Network Fizzy System ANFIS. Python Basic Python Advanced:   Numpy  Pandas Pandas  Matplotlib   Scikit-learn   The…

Source: Plan: Introduce the Softwares for Machine Learning

I am not sure when I could finish these, but I will try.