Parallel Barnes-Hut t-SNE implementation written in Rust.
bhtsne now supports parallelism, custom data types and custom user defined metrics.
Tensors and dynamic neural networks in pure Rust.
After reading most of the book, I wanted to get my hands dirty. My initial idea was to build a small machine learning framework but I deemed it to be too difficult if not impossible for me at the time. (Now, neuronika would have something to say). When gathering the bibliography for my thesis, I recalled to have stumbled upon a particular algorithm, t-SNE, whom I liked very much. I found the idea behind it to be very clever and elegant (t-SNE it's still one of my favorite algorithms, together with backprop and SOM, I find manifold learning fascinating in general). "So be it", I said, and I began writing a mess of a code, that was basically a translation of the C++ implementation. Boy was it bad.
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Barnes-Hut t-SNE, a tree-accelerated algorithm for data visualization reaches 0.3.0
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