In this video, I walk through three real-world supervised machine learning projects focused on binary classification, using popular Kaggle datasets. We build and evaluate models for spam URL detection, SMS spam classification, and cybersecurity intrusion detection, covering the full machine learning pipeline—from data preprocessing and feature extraction to model training and performance evaluation. This hands-on tutorial is perfect for beginners and intermediate learners who want to understand how supervised ML is applied to text data, URLs, and security-related datasets in practical scenarios.
Kaggle Codes :
https://www.kaggle.com/code/amineipad/intrusiondetection
https://www.kaggle.com/code/amineipad/smsspamclass
https://www.kaggle.com/code/amineipad/urlfakevsreal
