amazon-reviews
There are 72 repositories under amazon-reviews topic.
scrapehero-code/amazon-review-scraper
A basic python 3 based web scraper for extracting reviews from Amazon. Built using Selectorlib and requests
MuhammedBuyukkinaci/TensorFlow-Sentiment-Analysis-on-Amazon-Reviews-Data
Implementing different RNN models (LSTM,GRU) & Convolution models (Conv1D, Conv2D) on a subset of Amazon Reviews data with TensorFlow on Python 3. A sentiment analysis project.
officialpm/scrape-amazon
🤩 Python Package for Scraping Amazon Product Reviews ✨
avivace/reviews-sentiment
Data analytics, exploration, sentiment analysis and topic analysis (LDA) on Amazon customer reviews. And cool interactive plots.
VaibhavAbhimanyooHiwase/Sentimental_Analysis_using_Opinion_Target_and_Opinion_Words
This project performed sentimental analysis based on opinion words (like good, bad, beautiful, wrong, best, awesome, etc) of selected opinion target ( like product name for amazon product reviews).
pranitbose/sentiment-analysis
Sentiment Analysis of product based reviews using Machine Learning Approaches. This is my Final Year B.Tech Project, 2018.
hiteshvaidya/sentiment_analysis
Sentiment analysis on mobile phone reviews on amazon.
csbanon/bert-product-rating-predictor
The BERT Product Rating Predictor is a natural language processing model based on the Bidirectional Encoder Representations from Transformers (BERT) model developed to predict star ratings for textual product reviews. 2020.
kawsarlog/amazon-reviews-extraction
🛍️📊 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. 🐍🔍
alexliqu09/Sentiment-Analysis-on-Amazon-Reviews
In this project, we compared Spanish BERT and Multilingual BERT in the Sentiment Analysis task.
krpintu/amazonScraper
This package allows you to search for products on Amazon and extract some useful information (ratings, number of comments).
sid-ramakrishnan/AmazonReviewSummary
Abstractive and Extractive summarization of Amazon Reviews. Chrome extension front end
styfeng/SMERTI
Code for SMERTI for Semantic Text Exchange.
Kavitha-Kothandaraman/Product-Recommendation-Systems
To build a recommendation system to recommend products to customers based on the their previous ratings for other products
NikhilGupta1997/Sentiment-Analysis
Implementation of classical SVM and deep Seq-to-Seq LSTM models to analyze and classify sentiment (1-5 scale) on Amazon reviews.
iamirmasoud/amazon_sentiment
Sentiment Analysis on Amazon Reviews Dataset in PyTorch
lukasmoldon/genderBERT
Deep learning model for gender classification on texts using pretrained BERT models
aouataf-djillani/Amazon-review-sentiment-analysis
Vader Versus SVM and Logistic Regression for sentiment analysis
hechmik/amazon_reviews
Creation of a sentiment classifier on Amazon Reviews and evaluation on Twitter corpus
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.
jakobowsky/amazon-reviews-scraper
Amazon reviews scraper
sushil-rgb/AmazonBuddy
AmazonBuddy: Your Discord companion for instant product info extraction! Effortlessly retrieve ASIN/ISBN from links and access detailed reviews. Streamline your product research now!
tohid-yousefi/Sentiment_Analysis_on_Amazon_Product_Reviews
In this section, we will do a sentiment analysis on amazon product reviews.
vaibhavz2402/abstractive-text-summarization
Abstractive Text Summarization of Amazon reviews. Using LSTM model summary of full review is abstracted
Fabi8997/amazon-review-summarizer
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.
keswani-Rohitkumar/Deception_Detection_of_Amazon_Reviews
Classification for Deception Detection on Amazon Reviews Dataset
msiddhu/sentiment-analysis_on_phone-reviews
Sentiment Analysis using LSTM model on the smartphone reviews. Which are are scarped from amazon.in .
msikorski93/Sentiment-Analysis-on-Amazon-Reviews
A basic NLP project on musical instruments reviews on Amazon.
sherlvick/sentimental-analysis_SVM
Sentiment analyis of Amazon product reviews using SVM 'rbf':kernel classifier in which word vectorization is done using TF_IDF and CountVectorizer.
subhamyadav580/Amazon-Reviews-Predictions-of-Cell-Phones-and-Accessories
This project show the data visualisation of AMAZON Review dataset of Cell Phone and Accessories. It also shows the prediction of ratings according to there comments or reviews.
Abhi575k/sentiment-analysis
This ML model trains from data collected from Amazon product reviews and predicts whether the review is positive [1] or negative [-1].
AndreaZoccatelli/Sentiment_analysis
Scraping, visualizations and dictionary based sentiment analysis on Amazon reviews
jayasurya247/Sentiment-Analysis-on-Amazon-Fine-Food-Reviews
Sentiment Analysis on Amazon Fine Food Reviews
Rahulraj31/NLP_Review_SportsAndOutdoor
Performing NLP on Amazon's review on sports and outdoor
rositx/amazon-product-reviews-analysis
Uncover what customers love & dislike with sentiment analysis & topic modeling. Benchmark products & gain actionable insights to improve customer experience! #ecommerce #datascience
vaitybharati/Assignment-11-Text-Mining-Amazon-Reviews-using-Scrapy
Text-Mining-Amazon-Reviews-using-Scrapy. Ever wondered? Life would be easier if there could be ways to know how well your product performs and what do people feel about your product? The Solution -Text Mining Techniques. https://medium.com/@vaitybharati/text-mining-how-to-extract-amazon-reviews-using-scrapy-5bd709cb826c