https://github.com/khadkarajesh/recommender-system

Implicit Event Based Recommendation Engine for Ecommerce
https://github.com/khadkarajesh/recommender-system

ecommerce flask flask-restful heroku implicit lightfm postgresql python recommender-system sklearn streamlit surprise

Last synced: 27 days ago
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Implicit Event Based Recommendation Engine for Ecommerce

• Host: GitHub
• URL: https://github.com/khadkarajesh/recommender-system
• Owner: khadkarajesh
• Created: 2022-01-28T16:40:13.000Z (almost 3 years ago)
• Default Branch: master
• Last Pushed: 2022-02-05T19:14:14.000Z (almost 3 years ago)
• Last Synced: 2024-05-01T15:05:19.416Z (6 months ago)
• Topics: ecommerce, flask, flask-restful, heroku, implicit, lightfm, postgresql, python, recommender-system, sklearn, streamlit, surprise
• Language: Python
• Homepage: https://share.streamlit.io/khadkarajesh/recommender-system
• Size: 16.9 MB
• Stars: 3
• Watchers: 4
• Forks: 1
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

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README

        
# Recommender System

It is ecommerce based recommendation engine built on operational data one of the ecommerce application. It uses the hybrid approach to recommend products. Hybrid approach combines both attribute of user, items to solve the problem of cold start and data sparsity. User attributes: Age, Gender and Items attributes: Price, Brand, Category has been considered along with interaction's purchase, click, wishlist to built model

## Used Technologies

* Flask

* Python

* Streamlit

* Postgresql

## Steps to Run Application

1. [Install Dependencies](#install-dependencies)

2. [Run API](#run-api)

3. [Run Frontend](#run-frontend)

### Install Dependencies

1. Create a virtual environment with python3

   ```shell

   python3 -m virtualenv venv

   ```

2. Activate the virtual environment:

   ```shell

   cd venv

   source /bin/activate

   ```

2. Install dependencies

   ```shell

   pip install -r requirements.txt

   ```

### Run API

1. Configure the database Create database and add .env file in ```api/.env```. template of ```.env``` is as follows:

   ```shell

   DATABASE_NAME =

   DATABASE_PORT =

   USER_NAME =

   USER_PASSWORD =

   ```

2. Navigate to root of the project

3. Set environment variables

   ```bash

   export FLASK_APP=app:create_app

   export APP_SETTINGS="api.config.DevelopmentConfig"

   ```

4. Run Flask

   ```bash

   flask run

   ```

### Run Frontend

1. Run streamlit application as:

```bash

   streamlit run streamlit_app.py

```