There are 1 repository under customer-reviews topic.
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
Epinions Annotated Reviews Dataset
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.
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
Official Fera API ruby SDK gem to make interfacing with your business's reviews easy.
Fera.ai Magento 2 Extension
OpenTable Reviews Classification with BERT and Transfer Learning
Big Data Projects
The project aiming to extract product defects and opinions from customer reviews by using text clustering and sentiment analysis.
NLP demos and talks made with Jupyter Notebook and reveal.js
"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.
Case Analysis using ML methods to gain insight into customer reviews.
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
I developed an application that collects customer reviews automatically from online vendors. This tool's purpose is to get data easily for tasks such as text mining, classification, topic modeling, etc. The application's code is highly adaptable to any website thanks to its functional modularity.
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.
A simple design of a Restaurants Menu.
Synchronisation des commandes Thelia 2 vers la plateforme de récolte d'avis client KingAvis.
This project uses data from Olist - a Brazilian e-commerce platform to predict customer's review scores. The full Python code is presented in 3 steps: data preprocessing, EDA & modeling, followed by a Tableau Dashboard on customer ratings.
Analyzed ice cream customer reviews using NLP. Assessed product performance. Built an interactive R Shiny app to allow for tailored insights.
This project is part of my Consumer Sentiment Analysis class at Towson University, focusing on evaluating and understanding customer feedback on Spotify. By analyzing customer reviews sourced from Kaggle, we aim to extract insights into user satisfaction and areas of improvement for Spotify.
Welcome to the Customer Satisfaction Prediction Project repository! This project analyzes customer satisfaction survey to predict whether a customer is satisfied or dissatisfied based on various features. The goal is to gain insights into factors that contribute to passenger satisfaction and to build a predictive model for future.
NLP: topic modelling using BERTopic + LSA + pLSA + LDA
Project: Indian Restaurant Website with HTML CSS JavaScript. Created at https://spectra.codes, which is owned by @Drix10