this is my repository for Amazon review helpfulness prediction model
Customer Review Analysis is a prototype open source platform to turn the customer feedbacks in to visualization and extract the trending keywords.
Full stack web application for restaurant billing management system
Scraping functions for (1) Amazon customer reviews and (2) product information from best sellers list
This demo repository demonstrates how to analyze customer reviews with Azure OpenAI Service (AOAI). I leveraged "ASOS Customer Review" from Kaggle to obtain valuable insight from the customer review content.
Epinions Annotated Reviews Dataset
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.
A tool for analyzing Google Play Store reviews
OpenTable Reviews Classification with BERT and Transfer Learning
Fera.ai Magento 2 Extension
The project aiming to extract product defects and opinions from customer reviews by using text clustering and sentiment analysis.
Big Data Projects
Official Fera API ruby SDK gem to make interfacing with your business's reviews easy.
Case Analysis using ML methods to gain insight into customer reviews.
"ProLyzer" is a system which will guide you about the product you want to buy and also help the manufacturer/sellers to know the public opinion about their product's features.
NLP demos and talks made with Jupyter Notebook and reveal.js
This project aims to analyze consumer sentiment towards (FMCG) company products by scraping reviews & performing text analysis using Python. By leveraging NLP techniques, such as sentiment analysis, word cloud and topic modelling. The results of this study can inform product development, marketing strategies & overall business decision-making
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.
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