ayushidalmia/tsne-tensorboard-visualisation
This repository provides a starter code for using tensorboard via tensorflow for visualising embeddings
This tool helps machine learning engineers and researchers visualize complex, high-dimensional data, such as word or image embeddings. You input your embedding vectors and corresponding labels (like image filenames or text categories), and it generates an interactive t-SNE plot using TensorBoard. This allows you to explore relationships and clusters within your dataset, making it easier to understand the structure of your data.
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Use this if you need to quickly generate and explore t-SNE visualizations of your machine learning embeddings to identify patterns or anomalies.
Not ideal if you need to analyze data types other than embeddings or require advanced statistical analysis beyond t-SNE.
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Language
Python
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Last pushed
Apr 04, 2018
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