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A structured attempt to understand the concepts of recommendations and personalization through the final project in the course IEORE4571_001 - Personalization: Theory & Applications

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hritik25/Yelp-Restaurant-Recommendations

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This repository contains the following files -

  1. Report.pdf - Contains our final project report, which explains our objectives, sampling strategy, metrics and models used, results, limitations and conclusion. The report does not contain our EDA and model exploration, which is covered inside our notebooks.
  2. 01_data_wrangling_eda.ipynb - Contains the code for sampling and EDA of our project.
  3. 02_wide_and_deep.ipynb - Contains the code for our Wide and Deep model implementation.
  4. 03_FFM.ipynb - Contains the code for our Field Aware FFM implementation.
  5. requirements.txt - a list of python modules, packages and libraries used in the project

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A structured attempt to understand the concepts of recommendations and personalization through the final project in the course IEORE4571_001 - Personalization: Theory & Applications

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