I want to develop a recommendation system using Django(backend), React (frontend), Mongo Db

I want to develop a recommendation system using Django(backend), React (frontend), Mongo Db .

I need your suggestion and a guide me to integrarting React with Django

To create a recommendation system in Django, you can follow these steps:

  1. Setting up the Environment: Ensure you have Python, Django, Django Rest Framework, CORS and the required libraries installed. You can set up a virtual environment to keep your project dependencies isolated. DRF is highly needed to serialize/deserialize your data efficiently from client side and to be well utilized on your React.
  2. Understanding AI Recommendation Systems: Recommendation systems typically fall into two categories: content-based and collaborative filtering. For this tutorial, we’ll focus on content-based recommendations using the Prophet library for forecasting.
  3. Using Prophet for Forecasting: Prophet is a powerful forecasting tool developed by Facebook for time series data. It’s particularly useful when dealing with trends and seasonal patterns. We’ll leverage Prophet’s capabilities to predict user preferences and interests.
  4. Integrating Prophet with Django: Load historical data into Django models and preprocess the data. Create a function that generates recommendations for a specific user based on their historical activity.

For a detailed tutorial on how to build an AI recommendation system with Django and Prophet, you can refer to this [Medium article] (How to make an Ai recommendation system with Django and Prophet | by Ahmedtouahria | Django Unleashed | Aug, 2023 | Medium).

Please note that building a recommendation system involves advanced concepts in machine learning and data analysis. It’s recommended to have a good understanding of Python, Django, and the basics of machine learning before diving into this project.

For more info:

benfred/implicit: Fast Python Collaborative Filtering for Implicit Feedback Datasets (github.com)