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What is Unsupervised Learning (UL)?
Unsupervised learning is similar to machine learning, the difference being that the algorithm is not provided with any pre-assigned labels or scores for the training data. This technology lets machines learn on their own.
Labeling data is a labor-intensive task and requires a lot of time, and in several cases, it is just not viable. This is where unsupervised learning comes into the picture by giving AI applications the ability to learn without labels and commands. Moreover, it allows AI applications to learn and find hidden patterns in huge datasets. Besides, it is useful for achieving artificial general intelligence.
Unsupervised machine learning is a revolutionary breakthrough technology that provides machines with a self-learning system and the ability to accumulate experience. In this case, it can save programmers from coding for different programs and apps. For example, unsupervised machine learning is widely used in cybersecurity. It can build up a system for machines to detect the threats against the system by itself. Since the threats against cybersecurity change quickly, the traditional methods against network viruses are no longer effective. Therefore, we need unsupervised learning to protect cybersecurity.
