URI-URL Classification using Recurrent Neural Network, Support Vector and RandomForest. The Implementation results follows with classification report, confusion matrix and precision_recall_fscore_support for each validation result of a 10-fold crossval

To identify and extract features from URL that help classify URLs into benign/phishing and train an ML model with these features for classification.

Machine Learning model for URL Reputation dataset from UCI ML Repository

URL classification by Naive Bayes algorithm

Proactive Malicious URL Detection: ML Defense 🌐🛡️"

Identifying Suspicious URLs: An Application of Large-Scale Online Learning (Python Reproducibility Experiment)

multi-label url classification

Multi-label URL Classification

QuickCharNet is a deep learning project that leverages an efficient character-level Convolutional Neural Network (CNN) for URL classification, aimed at enhancing Search Engine Optimization (SEO). The project includes datasets, model evaluation notebooks, and visualization scripts. Key features include data preprocessing, detailed model architecture