huzaifakhan04/amazon-product-recommendation-system-web-application-using-mongodb-pyspark-and-apache-kafka
This repository includes a web application that is connected to a product recommendation system developed with the comprehensive Amazon Review Data (2018) dataset, consisting of nearly 233.1 million records and occupying approximately 128 gigabytes (GB) of data storage, using MongoDB, PySpark, and Apache Kafka.
This project helps e-commerce businesses provide personalized product suggestions to their customers. It takes a massive dataset of past purchases and reviews, then outputs specific product recommendations tailored to individual users. This is ideal for e-commerce managers, marketing teams, or business strategists looking to improve customer experience and sales.
No commits in the last 6 months.
Use this if you need to build or implement a system that suggests relevant products to customers based on their history and the behavior of other shoppers.
Not ideal if you're looking for a simple, off-the-shelf plugin for an existing e-commerce platform or if your data volumes are small enough for manual analysis.
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BSD-3-Clause
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Last pushed
Jun 26, 2023
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