A two-tower, deep learning recommender system that learns embeddings for users and tutors on a (currently) randomly generated dataset. Tower one employs collaborative filtering to generate positive and negative samples while tower two utilizes a modified version of word2Vec to learn embeddings on prior tutor usage data. Supports embedding visualization based on user features and an adjustable representation of features as numbers.
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A recommender system matching tutors and students.
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qiud1/Tutor-Recommender
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A recommender system matching tutors and students.
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