It includes 3 machine learning models
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The first is a Credit Card Fraud Detector. The model is built using a dataset of historical transactions, where the task is to identify whether a transaction is legitimate or fraud based on various features. Random Forest Classifier has shown a higher accuracy.
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The second is a Movie Genre Classifier. It is trained using a dataset of movie information, including plot summaries, metadata and other relevant attributes. Different machine learning algorithms have been explored and evaluated for optimal performance such as Logistic Regression, SVC, Naive Bayes and the model performed with an accuracy of 58.72%
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The third is a SPAM SMS Detector. It is trained on a dataset of labeled SMS messages, using text features to identify patterns and make accurate predictions. Several models are tested which includes Linear SVC, Logistic Regression and XG Boost where SVC and XG Boost showed higher accuracies outperforming Logistic Regression.