How does machine learning improve spam filtering?

How does machine learning improve spam filtering?

Machine learning enhances spam filtering by analyzing patterns in emails to identify spam more accurately.

What algorithms are commonly used in spam filtering?

Common algorithms include Naive Bayes, Support Vector Machines, and neural networks.

Can machine learning adapt to new spam techniques?

Yes, machine learning models can be trained continuously to adapt to new spam techniques and improve their accuracy.

What are the challenges in implementing machine learning for spam filtering?

Challenges include dealing with false positives, evolving spam tactics, and the need for large labeled datasets.