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Using NLP and artificial intelligence to help Cornell students discover classes that align more with their interests.

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Semantic Classes

Students attend college to learn, grow, and discover new fields of study, and yet there is currently no technological solution for students to find new classes.

demo

The existing class roster merely provides a keyword-match search, so if students don't know precisely what they're looking for it's hard for them to find subjects they may be interested in.

This project aims to address this problem by using NLP Techniques such as Word Embeddings to recommend classes to students based on the semantic similarity of ther interests.

This repository contains the frontend, backend, and ML (notebook) code used in the project, hosted at cornellcourses.org

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Using NLP and artificial intelligence to help Cornell students discover classes that align more with their interests.

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