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🛍️📊 Effortlessly extract Amazon reviews using Python with the amazon-reviews-extraction script. This script makes use of popular Python modules like requests, pandas, bs4, and lxml to scrape and parse HTML content from Amazon product review pages. Simplify your data extraction process and gain valuable insights from customer reviews. 🐍🔍
Uncover what customers love & dislike with sentiment analysis & topic modeling. Benchmark products & gain actionable insights to improve customer experience! #ecommerce #datascience
AmazonBuddy: Your Discord companion for instant product info extraction! Effortlessly retrieve ASIN/ISBN from links and access detailed reviews. Streamline your product research now!
Repository containing the project for the course on Business and Project Management at the University of Pisa (A.Y. 2022/2023) realized by Fabiano Pilia, Emanuele Tinghi and Matteo Dal Zotto.
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 repository showcases the outcomes of an Exploratory Data Analysis (EDA), including visualisation, conducted on 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 and PySpark.