sanjeebtiwary/E-Commerce-Product-Recommendation
E-commerce businesses are always striving to provide personalized experiences to their customers to increase engagement and loyalty. One way to achieve this is through product recommendation systems. In this project, we will build a recommendation system for an e-commerce website using batch processing and stream processing techniques.
This project helps e-commerce businesses provide personalized shopping experiences to their customers. It takes user behavior data like clicks, purchases, and page views, along with real-time browsing activity, and generates tailored product recommendations. E-commerce managers, marketing teams, and store owners would use this to boost engagement and sales.
No commits in the last 6 months.
Use this if you want to implement a system that suggests relevant products to your online shoppers based on their past actions and current browsing.
Not ideal if you are looking for a simple, static 'most popular' products list without needing dynamic, personalized recommendations.
Stars
10
Forks
2
Language
Jupyter Notebook
License
GPL-3.0
Category
Last pushed
May 26, 2023
Commits (30d)
0
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