Unsupervised machine learning is a type of machine learning that does not require labeled data. This means that it can be used to analyze data that does not have any known categories or labels. This makes unsupervised machine learning ideal for cybersecurity applications, as it can be used to identify anomalies and threats in data that would be difficult or impossible to detect with traditional methods.
In this video, we will discuss the use of unsupervised machine learning in cybersecurity. We will cover the following topics:
What is unsupervised machine learning?
How can unsupervised machine learning be used in cybersecurity?
What are some of the challenges of using unsupervised machine learning in cybersecurity?
What are some of the benefits of using unsupervised machine learning in cybersecurity?
We will also discuss some of the recent advances in unsupervised machine learning that are making it more powerful and effective for cybersecurity applications.
