amazon-review-dataset

Scrape Amazon reviews with ScrapingBee's API, proxy rotation, and JavaScript rendering. Outputs name, rating, date, title, body to CSV.

To build a recommendation system to recommend products to customers based on the their previous ratings for other products

Rate Prediction using Amazon Review Dataset and Deep Learning

Data Mining on Amazon user reviews for musical instruments

This repository contains code and resources for analyzing Amazon reviews and performing sentinent analysis.

Sentiment analysis of amazon reviews dataset using BERT - model development and deployment

Assignments for MSCI 641: Text Analytics, Spring 2020 at University of Waterloo.

This notebook will show you how to implement a deep leaning algorithm (LSTM) on the Amazon Alexa Reviews dataset

The public dataset in Hindi language published for paper 28 - AICS2020, Ireland

Analysing Amazon customer reviews via Clustering, Visualization and Classification

Sentimentally analyze product reviews to predict opinion honesty.

Performing NLP on Amazon's review on sports and outdoor

Predicting polarity of Amazon user reviews using Deep Learning 🎭

Sentiment Analysis using Conv1D and LSTM

A simple sentiment analysis using SGD and LinearSVC for Amazon Reviews

Generating synthetic reviews from real reviews by fine tuning pretrained GPT 2 117M model, followed by few-shot prompting, finally evaluating by BERT classifier.

This project aims to create a pipeline-architecture for applying sentiment analysis to reviews on an amazon dataset.

Sentiment analysis of Amazon product reviews using classical machine learning and transformer-based NLP models.

Sentiment Analysis is the process of determining whether a piece of writing is positive, negative or neutral.

MapReduce to calculate the Chi-squared value for the Amazon Review Corpus