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UCLA STATS 199 - Independent Directed Research


Topic Distribution and Similarity in Online Publications

This repository contains the code and data for my Spring/Summer 2018 STATS 199 class with Professor Miles Chen. This project concerns the distribution of topics - e.g. immigration or healthcare - and how they are identified, with an emphasis on easily interpretable methods. Additionally, this project explores other more abstract, less interpretable methods, such as variational autoencoders and word embeddings, which are both various forms of dimensionality reduction.

The code can be found in the notebok proj.ipynb.

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