Official Fera API ruby SDK gem to make interfacing with your business's reviews easy.
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Updated
Jan 6, 2024 - Ruby
Official Fera API ruby SDK gem to make interfacing with your business's reviews easy.
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.
OpenTable Reviews Classification with BERT and Transfer Learning
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.
NLP demos and talks made with Jupyter Notebook and reveal.js
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.
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
Full stack web application for restaurant billing management system
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.
The project aiming to extract product defects and opinions from customer reviews by using text clustering and sentiment analysis.
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.
Customer Review Analysis is a prototype open source platform to turn the customer feedbacks in to visualization and extract the trending keywords.
Analyzed ice cream customer reviews using NLP. Assessed product performance. Built an interactive R Shiny app to allow for tailored insights.
A simple design of a Restaurants Menu.
Synchronisation des commandes Thelia 2 vers la plateforme de récolte d'avis client KingAvis.
A tool for analyzing Google Play Store reviews
Case Analysis using ML methods to gain insight into customer reviews.
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