Visualizing word similarities in Adventures of Huckleberry Finn using TSNE
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Updated
Jun 22, 2017 - Python
Visualizing word similarities in Adventures of Huckleberry Finn using TSNE
Dimensionality reduction and visualization techniques t-stochastic neighbour embedding (t-SNE) and uniform manifold approximation and projection (UMAP) were used to evaluate National Renewable Energy Laboratory’s (NREL) market segmentation for rooftop solar technical potential based on small, medium, and large classification labels. The medium a…
Deep-based generation of Wing Interferential Patterns Images for the surveillance of blood-sucking insect population by Machine learning algorithms(Generative adversarial networks, Adversarial Autoencoders). Summer intership, research project
My Dissertation evaluates methods against S&P 500 US stock data from Yahoo Finance, aiming to offer a concise financial market snapshot
kernalized t-Distributed Stochastic Neighbor Embedding (t-SNE)
The project visualizes the high dimensional bioacoustic data in 2D scatter plot using the tSNE technique.
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Implementation of t-SNE and Barnes-Hut-SNE algorithm. Comparison of algorithm implementation with sklearn library implementation on sample databases.
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Fast Barnes-Hut t-SNE with Tensorflow integration
CUDA-accelerated PyTorch implementation of t-SNE
A python wrapper for Barnes-Hut tsne: for Python >= 3.5
Pytorch implementation for t-SNE with cuda to accelerate
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