# T-SNE

### Stochastic Neighbor Embedding

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T-SNE is a machine learning algorithm for data visualization (usually), which is based on a nonlinear dimensionality reduction technique. 
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The basic idea of t-SNE is to reduce dimensional space keeping relative pairwise distance between points. In other words, the algorithm maps multi-dimensional data to two or more dimensions, where points which were initially far from each other are also located far away, and close points are also converted to close ones. 

> It can be said that t-SNE looking for a new data representation where the neighborhood relations are preserved.

### References

{% embed url="<https://towardsdatascience.com/google-news-and-leo-tolstoy-visualizing-word2vec-word-embeddings-with-t-sne-11558d8bd4d>" %}