businessrecommender

• Bellow is the summary of files. To run this, you will need api key / env to pipecone, and download yelp dataset to google collab. Happy coding
  • the yelp sample dataset is from https://www.yelp.com/dataset
  • notebook to parse the yelp data files and inject into pipecone vector db
    • yelprecommender_pipeconeinjection.ipynb
  • notebook to train ranking model using pointwise mse loss and save the model for download
    • yelpbusiness_ranking_using_mse_loss.ipynb
  • the ranking model in zip : businessexport-20230626T234723Z-001.zip
    • this is the model trained using pointwise tensorflow recommender with Yelp sample data
  • the notebook to download the model and retrieve and then rank the vendors
    • getyelprankingusingpipeconeandrecommender.ipynb
    • you will need the Pipecone api key and env to run this