Machine Learning: Possibilities and limitations of unsupervised learning

Unsupervised learning is a Machine Learning technique that can detect patterns and relationships in data without relying on a pre-existing pattern. Unlike supervised learning, which trains an algorithm based on labeled data, unsupervised learning works with unlabeled data that is not characterized by a specific category or objective. In this way, new insights can be gleaned from the data that may not be detected using other methods. In this blog post, you will learn about the potential applications for unsupervised learning and the challenges we currently face.


How does Machine Learning actually work?

Machine Learning is undoubtedly one of the most exciting subfields of Artificial Intelligence. It performs the task of learning from data with specific inputs for the machine. It is important to understand how Machine Learning works and what types of it exist. Therefore, this blog post will shed light on how Machine Learning is fundamentally designed to create targeted value for users.


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