Malware Detection using Machine Learning

Malware poses a risk to Windows computers, and antivirus software frequently fails. This project detects malware using machine learning, more precisely a Decision Tree. Without opening the programs, it examines information from executable files [PE], such as headers, sections, import tables, and entropy. The Decision Tree uses the CSV files to learn and make predictions. The end product is a quick, dependable system that can instantly determine if a file is malicious or safe.