Unsupervised domain adaptation with BERT for Amazon food product reviews sentiment analysis.
Sentiment analyzer that predicts the review star ( from 0 to 5, continuously) of given food text review.
🧐 This project analyzes Amazon Fine Food Reviews to investigate whether negative reviews are more emotionally intense and lexically repetitive than positive ones. Using R, we apply sentiment analysis and lexical diversity metrics to uncover patterns in consumer review language.
Amazon Fine Foods Review
Amazon_Food_Reviews_Model_Deployment using web app by Heroku platform and built using Flask.
A Python NLP project comparing rule-based sentiment classification with VADER and transformer-based models from 🤗 Huggingface. This project analyzes Amazon customer reviews to evaluate sentiment classification performance across traditional and deep learning approaches.
Implementation of Machine learning algorithms KNN, Naive Bayes, Logistic Regression, SGD for linear regression, SVM, Decision Trees,Random Forest,k means and Truncated SVD on Amazon fine food reviews data set
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