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  2. t-distributed stochastic neighbor embedding - Wikipedia

    en.wikipedia.org/wiki/T-distributed_stochastic...

    t-distributed stochastic neighbor embedding (t-SNE) is a statistical method for visualizing high-dimensional data by giving each datapoint a location in a two or three-dimensional map. It is based on Stochastic Neighbor Embedding originally developed by Geoffrey Hinton and Sam Roweis, [ 1 ] where Laurens van der Maaten and Hinton proposed the t ...

  3. Dimensionality reduction - Wikipedia

    en.wikipedia.org/wiki/Dimensionality_reduction

    T-distributed Stochastic Neighbor Embedding (t-SNE) is a nonlinear dimensionality reduction technique useful for the visualization of high-dimensional datasets. It is not recommended for use in analysis such as clustering or outlier detection since it does not necessarily preserve densities or distances well.

  4. Nonlinear dimensionality reduction - Wikipedia

    en.wikipedia.org/wiki/Nonlinear_dimensionality...

    t-distributed stochastic neighbor embedding (t-SNE) [26] is widely used. It is one of a family of stochastic neighbor embedding methods. The algorithm computes the probability that pairs of datapoints in the high-dimensional space are related, and then chooses low-dimensional embeddings which produce a similar distribution.

  5. OpenShot - Wikipedia

    en.wikipedia.org/wiki/OpenShot

    OpenShot Video Editor is a free and open-source video editor for Windows, macOS, Linux, and ChromeOS. The project started in August 2008 by Jonathan Thomas, with the objective of providing a stable, free, and friendly to use video editor.

  6. Tutte embedding - Wikipedia

    en.wikipedia.org/wiki/Tutte_embedding

    In graph drawing and geometric graph theory, a Tutte embedding or barycentric embedding of a simple, 3-vertex-connected, planar graph is a crossing-free straight-line embedding with the properties that the outer face is a convex polygon and that each interior vertex is at the average (or barycenter) of its neighbors' positions.

  7. TensorFlow - Wikipedia

    en.wikipedia.org/wiki/TensorFlow

    [5] [6] It is free and open-source software released under the Apache License 2.0. It was developed by the Google Brain team for Google 's internal use in research and production. [ 7 ] [ 8 ] [ 9 ] The initial version was released under the Apache License 2.0 in 2015.

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