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Fake News Detection System with NLP Analytics
Machine LearningThe Fake News Detection System is a Flask-based web application that uses Machine Learning and NLP to classify news content as Real or Fake. Users log in securely and submit news text for analysis. The system processes the input using a pre-trained ML pipeline and provides prediction results along with a confidence score. To enhance transparency, the application also generates text analytics, including word count, character count, sentiment polarity, and subjectivity using TextBlob. This makes the system not only a classifier but also an insightful tool for understanding news tone and credibility. The project demonstrates the practical application of NLP, text preprocessing, and probabilistic ML models in combating misinformation and can be extended for journalism, media monitoring, and content verification platforms.
Career Recommendation System Using Machine Learning
Machine LearningThis project is a machine learning–based career recommendation system built using Python and Flask. It predicts a suitable job role based on a user’s skills, interests, certifications, and personal attributes. A Decision Tree model is used to analyze input data and generate predictions with a confidence score. The web application provides an easy-to-use interface for real-time career guidance.