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:
- 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.
- 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.
- 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.
- 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)