The primary objective of this project is to equip users with a powerful Machine Learning-driven application to proactively defend against phishing threats and identify malicious URLs. By leveraging a range of ML algorithms, including decision trees, Random Forests, MLP, SVM, XGBoost algorithm, and more, our robust model ensures accurate detection.
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The primary objective of this project is to equip users with a powerful Machine Learning-driven application to proactively defend against phishing threats and identify malicious URLs. By leveraging a range of ML algorithms, including decision trees, Random Forests, MLP, SVM, XGBoost algorithm, and more, our robust model ensures accurate detection.
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Sandeep9975/sitespurified
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The primary objective of this project is to equip users with a powerful Machine Learning-driven application to proactively defend against phishing threats and identify malicious URLs. By leveraging a range of ML algorithms, including decision trees, Random Forests, MLP, SVM, XGBoost algorithm, and more, our robust model ensures accurate detection.
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