In this project we use sklearn and CUDA to show an example of t-SNE algorithm. t-Distributed Stochastic Neighbor Embedding (t-SNE) is a technique for dimensionality reduction that is particularly well suited for the visualization of high-dimensional datasets.
We used a CNN to generate high-dimensional features from images and then show how they can be projected and visualized into a 2-dimensional space using t-SNE.
|Multi-language:||Python & C++|
|Training time:||+67% (over baseline)|
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