Machine learning enhances malware detection by analyzing file characteristics, behavioral patterns, and network communications to identify threats. Static analysis examines file properties without execution, while dynamic analysis observes runtime behavior in controlled environments. Ensemble methods combining multiple algorithms improve detection accuracy and reduce false positives. AI-powered systems can identify zero-day threats and polymorphic malware that traditional signature-based solutions miss.