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).
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Updated
Jul 26, 2018 - Python
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).
LADy 💃: A Benchmark Toolkit for Latent Aspect Detection Enriched with Backtranslation Augmentation
Extract customer reviews from some online stores and classify negative reviews.
An AI solution which cognitively able to detect(classify) reviews in fractions of seconds. hence, fewer human interventions, more precise, uniform results, and most importantly operational efficiency.
Analysing Amazon customer reviews via Clustering, Visualization and Classification
Review Analysis (NLP) of musical instrument reviews from the amazon dataset. Observing performances of Linear SVC, NaiveBayes (MultinomialNB) , Random Forest Classifier and Logistic Regression under use of Count and tf-idf vectorizers.
Analysing reviews with the help of NLP
Descriptive and predictive analyses of Amazon Fine Food Reviews dataset.
This project uses Machine Learning, Natural Language Processing (NLP), and Web Scraping in order to get real customer reviews for any product on Amazon and perform sentiment analysis that predicts whether the reviews are positive or negative.
Get your scrapes in sync
The Amaon Fine Foods Review dataset consists of reviews of fine foods from Amazon. There are approximate 500,000 reviews up to October 2012. Reviews include product and user information, ratings, and a plain text review. The Aim of this case study was to predict the polarity of the reviews ie. positive/negative. I have applied various Machine Le…
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
Opinion classification with kili-technology and huggingface by fine-tuning roBERTa model.
Code of Play Store Review Analysis Project, and I gained some valuable insights from the play store dataset.
This has been done as a part of Data Science Career Track Course at Springboard.
Sentiment Analysis of Amazon Food Reviews to the customer ratings using VADER, TextBlob and Flair
In this project, we have analyzed the amazon alexa customer reviews with the help python libraries.
2021 Introduction-to-Information-Retrieval-and-Text-Mining Final Project
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