customer-reviews

There are 1 repository under customer-reviews topic.

• keisukeirie / Amazon_review_helpfulness_prediction

  this is my repository for Amazon review helpfulness prediction model

  amazoncustomer-reviewshelpful-reviewsnlp-machine-learningnmfprediction-modelproduct-reviewsrandom-forestxgboost-model
  Language:Jupyter Notebook 11
• Customer-Review-Analysis-SaaS

  arpan65 / Customer-Review-Analysis-SaaS

  Customer Review Analysis is a prototype open source platform to turn the customer feedbacks in to visualization and extract the trending keywords.

  nlpcustomer-reviewsdashdashboardaws
  Language:Jupyter Notebook 10

• Mak-3 / Restaurant-Billing-Management-system

  Full stack web application for restaurant billing management system

  customer-reviewshtml-css-javascriptmavenrestaurant-billing-managementrestaurant-managementspring-mvcweb-applicationwebappbootstrap5javasqltwilio-sms-api
  Language:JavaScript 8

• lhehnke / amazon-data

  Scraping functions for (1) Amazon customer reviews and (2) product information from best sellers list

  amazonrvestscraperweb-scrapingcustomer-reviewsr
  Language:R 7

• dokooh / epinions_annoreview_dataset

  Epinions Annotated Reviews Dataset

  datasetcustomer-reviewsannotationsnlprankingaspectsdiversitysummarizationrecommender-systemtopic-modelingtopic-model
  4

• easonlai / analyze_customer_reviews_with_aoai

  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.

  azureazure-cognitive-servicesazure-openaicustomer-retentioncustomer-review-categorizationcustomer-review-datasetcustomer-reviewsopenaiopenai-gpt3pythonpython3sentiment-analysistext-generationtext-summarization
  Language:Jupyter Notebook 4

• AtulJoshi1 / Market-Structure-Analysis-using-Online-customer-reviews

  market-structure-analysiscustomer-reviewsweb-scrapingbeautifulsoupclusterperceptual-mapbrandsattributesmarketingmachine-learningcorrespondence-analysispython3r
  Language:Jupyter Notebook 3

• 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.

  alsalternating-least-squaresamazonamazon-reviewsapache-kafkacustomer-reviewsflask-applicationinferential-statisticsmachine-learningmongodbnosqlproduct-recommendationsproduct-recommender-systemproduct-reviewspysparkspark-mllibstatistical-inferencesupervised-learningweb-application
  Language:Jupyter Notebook 3

• ianovski / google-play-store-nlp

  A tool for analyzing Google Play Store reviews

  customer-reviewsclassify-reviewsbertnlpw2vsparkdocker
  Language:Python 3

• tasnim31 / customer-review-summarization

  customer-reviewsnltkweb-crawlersentiment-analysis
  Language:Python 3

• feracommerce / fera-api-ruby

  Official Fera API ruby SDK gem to make interfacing with your business's reviews easy.

  api-clientbigcommercecustomer-reviewsferamagentomagento2railsreviewsrubyruby-gemrubygemshopifyugcuser-generated-contentwix
  Language:Ruby 2

• feracommerce / magento2_extension

  Fera.ai Magento 2 Extension

  customer-reviewsmagentomagento2magento2-extensionmagento2-moduleproduct-reviewsreviews
  Language:PHP 2

• issacchan26 / CustomerReviewClassificationWithBERT

  OpenTable Reviews Classification with BERT and Transfer Learning

  bertcustomer-reviewsnatural-language-processingnlpopentablerestaurant-reviewsreview-classificationsentiment-classificationtext-classificationtransfer-learningweb-scraping
  Language:Jupyter Notebook 2

• rsingh26 / DataScience

  Big Data Projects

  hadoophivepiglocalbusinesscustomer-reviewsdata-analysistext-analysissentiment-analysisvisualizationtutorialmachine-learningmachine-learning-algorithmsrprogrammingpython
  Language:HTML 2

• SevcanDogramaci / AmazonReviewProject

  The project aiming to extract product defects and opinions from customer reviews by using text clustering and sentiment analysis.

  sentiment-analysisnlpclusteringcustomer-reviews
  Language:Jupyter Notebook 2

• howard-haowen / NLP-demos

  NLP demos and talks made with Jupyter Notebook and reveal.js

  chinese-traditionalcustomer-reviewsforumsjupyter-notebookmachine-learningnlppca-analysispythonreavealjssentiment-analysisspacytext-classificationtext-similaritytfidf-vectorizertransformerword2vec-embeddinngs
  Language:Jupyter Notebook 1

• hybridlogics / prolyzer

  "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.

  opinionscustomer-reviewssentimental-analysismachine-learningmachine-learning-algorithmsreviewsratingstanford-nlpstanford-corenlpsentic-networdnetsentiwordnetfirebase
  1

• JacobMannix / classifying-amazon-reviews

  Case Analysis using ML methods to gain insight into customer reviews.

  case-analysiscustomer-reviewsmachine-learningpython3
  Language:Jupyter Notebook 1

• krishnavpai / Sentiment-Analysis-Word-Cloud-and-Topic-Modelling-on-customer-reviews-of-FMCG-products-in-India

  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

  customer-reviewslatent-dirichlet-allocationreview-analysissentiment-analysistext-analyticstopic-modelingwordcloudjupyter-notebookreview-datasetscraping
  Language:Jupyter Notebook 1

• bilge-karaca / Customer_Review_Scraping

  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.

  customer-reviewsparserreviewsscraperweb-scrapingwebscraping
  Language:Jupyter Notebook 0

• fadyabila / NLP-Restaurant-Review-Prediction

  customer-reviewsdeep-learningnlppython
  Language:Jupyter Notebook 0

• huzaifakhan04 / exploratory-data-analysis-on-amazon-review-data-using-mongodb-and-pyspark

  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.

  amazonamazon-reviewscustomer-analysiscustomer-reviewsdata-analysisdata-sciencedata-visualisationedaexploratory-data-analysisinferential-statisticsmongodbnosqlproduct-analysisproduct-reviewspysparkstatistical-analysisstatistical-inferencestatistics
  Language:Jupyter Notebook 0

• jLuseno161 / Anitas-Kitchen

  A simple design of a Restaurants Menu.

  foodsservicesdrinkscustomer-reviews
  Language:HTML 0

• KelvinLam05 / cleaning_primark_reviews

  webscrapingdata-preprocessingcustomer-reviews
  Language:Jupyter Notebook 0
• TheliaKingAvis

  kevinseebach / TheliaKingAvis

  Synchronisation des commandes Thelia 2 vers la plateforme de récolte d'avis client KingAvis.

  kingavistheliathelia-modulecustomer-reviewsphpsymfony
  Language:PHP 0
• Customer-Experience-Analysis-Dashboard

  trang-h-vo / Customer-Experience-Analysis-Dashboard

  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.

  machine-learninge-commerce-platformcustomer-reviewspython3random-forest-classifierxgboost-algorithmimbalanced-classification
  Language:Jupyter Notebook 0

• tysonpond / ice-cream-data-dashboard

  Analyzed ice cream customer reviews using NLP. Assessed product performance. Built an interactive R Shiny app to allow for tailored insights.

  customer-reviewsdashboardmarketingnlpproduct-managementrshinyweb-scraping
  Language:Jupyter Notebook 0

• ayushipandeyy / ayushipandeyy-Spotify-Customer-Review-Sentiment-Analysis

  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.

  customer-reviewsdatadata-cleaningmachine-learningmachine-learning-modelspythonsentiment-analysistokenizationvectorization
  Language:Jupyter Notebook

• Craniace / Customer_Review

  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.

  customer-reviewsdata-analysisgraphpredictionpredictive-analyticspythonreview
  Language:Jupyter Notebook

• MarionChaff / topic-modelling

  NLP: topic modelling using BERTopic + LSA + pLSA + LDA

  bertopiccustomer-reviewse-commerceldalsamachine-learningnatural-language-processingnlpplsapythontext-analysistopic-modelling
  Language:Jupyter Notebook

• spectra-ai-codegen / spice-odyssey-restaurant-website

  Project: Indian Restaurant Website with HTML CSS JavaScript. Created at https://spectra.codes, which is owned by @Drix10

  api-integrationcode-generationcode-qualitycustomer-reviewsdeveloper-toolsdevopsexpressjsfood-menuindian-restaurantjavascriptloyalty-programmachine-learningnextjsonline-orderingpostgresqlreservations-systemrestaurant-websitesoftware-developmenttailwindcss
  Language:JavaScript