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bagofwords

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This repository houses a Streamlit web application for fake news detection. The app allows users to input a news article and predicts whether it is likely fake or real based on its content. It provides options to select different vectorizers (TF-IDF or Bag of Words) and classifiers (Linear SVM or Naive Bayes) to customize the prediction model.

  • Updated May 10, 2024
  • Jupyter Notebook

Our team sought to perform sentiment analysis on Twitter tweets in anticipation for Hideo Kojima's video game release, Death Stranding, in 2019. We sourced the Tweets from two libraries, preprocessed them, stored them using MongoDB and then performed sentiment analysis.

  • Updated Feb 20, 2024
  • Jupyter Notebook

A spam classifier is a software or machine learning model that categorizes incoming messages or content as either "spam" (unwanted or irrelevant) or "ham" (legitimate or relevant), using automated techniques.

  • Updated Nov 30, 2023
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Review sentiment based on drug user reviews text/ dataset, using a supervised binary text classifier, which will classify user reviews as positive or negative

  • Updated Sep 14, 2023
  • Jupyter Notebook

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