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Project 2: Hybrid Neural Network Recommender

Project description

This project contains a recommender based on a neural network model. The goal is to achieve the best HR@10 in the final evaluation which is done with seed=6789.


Project structure

Project contains 4 main folders:

  • data (contains hotel data on which recommender is running)
  • data_processing (contains 3 python files, where you can find methods meant to help manage the original data)
  • evaluation_and_testing (contains 2 python files with testing and recommender evaluation)
  • recommenders (contains 8 python files, all are different kinds of recommenders)

There are 2 ".ipynb" files which contains code execution and they are main part of the project


Results

The best achieved result is on model 2 and HR@10 = 0.236253


Requirements to run the project

  1. Create (and activate) a new environment with Python 3.8.10

  2. Install all the libraries with command below

     pip install -r requirements.txt
    
  3. Start Jupyter Notebook and open files:

    • project_1_data_preparation.ipynb
    • project_2_recommender_and_evaluation.ipynb

This project was based on https://github.com/PiotrZiolo/recommender-systems-class.git repository, created by Piotr Zioło.

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Hybrid Neural Network Content Based Recommender

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