Dimensionality Reduction


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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