HondaPL / Recommending-Systems-Project

Content-Based Recommender - Adam Hącia 2022

Recommending Systems Project

Content-Based Recommender - Adam Hącia 2022

Table of contents

• Recommending Systems Project
  • Table of contents
  • Achieved results compared to Amazon Recommender
  • Project Description
  • Technologies
  • Setup
  • Status
  • Contact

Achieved results compared to Amazon Recommender

Project Description

Content-based recommender system that recommends products based on the content of the product description.

Technologies

• Python 3.9.7
• Anaconda + Jupyter

Setup

1. Install Anaconda with Python >= 3.8.
2. Prepare your conda environment
   • Run the following command: conda create -n recommender python=3.8
   • Activate the conda environment by running: conda activate recommender
3. Install the required packages
   • Run the following commands: conda install numpy conda install pandas conda install matplotlib conda install seaborn conda install sklearn conda install hyperopt
4. In Bash type: jupyter notebook The notebook will be opened in your browser.
5. In Jupyter Notebook open these files and run all cells: project_1_data_preparation project_1_recommender_and_evaluation
6. Last cell in project_1_recommender_and_evaluation.ipynb should contain the results of the evaluation with HR@10 metric for
   • LinearRegressionCBUIRecommender
   • AmazonRecommender
   • RandomForestCBUIRecommender
   • XGBoostCBUIRecommender

Status

Project is: completed

Contact

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