To build a recommendation system to recommend products to customers based on the their previous ratings for other products
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Updated
May 29, 2020 - Jupyter Notebook
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.
Assignments for MSCI 641: Text Analytics, Spring 2020 at University of Waterloo.
Sentiment analysis of amazon reviews dataset using BERT - model development and deployment
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
Sentiment Analysis using Conv1D and LSTM
Predicting polarity of Amazon user reviews using Deep Learning 🎭
Amazon Reviews Analysis
Apparel-recommendation-engine-Machine-Learning
Large Scale Text Classification on Amazon Reviews Corpus
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.
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
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