👉 Unsupervised learning is a type of machine learning where data is not labeled or classified, but instead it is used to discover patterns and relationships in the data without any explicit knowledge about the underlying structure. In other words, unsupervised learning doesn't require the presence of labels to learn anything meaningful from the data.
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What is the definition of Unsupervisedly? 🙋
👉 Unsupervisedly refers to a process or activity where the objective is not to find patterns, but rather to understand and analyze data without any explicit goal in mind. This can involve tasks such as clustering, classification, association rule mining, etc. In this context, "unsupervised" means that there is no pre-defined algorithm or model used for analysis. Instead, it's an approach where the data itself provides enough information to make sense of itself. The term comes from the field of machine
What is the definition of Unsupervised? 🙋
👉 Unsupervised refers to a type of machine learning technique that does not require any labeled data. It is an approach where the goal is to discover patterns or structures in unlabeled data without any prior knowledge about their structure. In other words, it's like finding hidden information within data without knowing what's there. Unsupervised algorithms can be used for tasks such as clustering, anomaly detection, classification, and dimensionality reduction, among others. Some examples of unsupervised learning techniques include: 1
