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Association rules are a type of unsupervised machine learning technique that helps find relationships between items in a dataset. Instead of predicting a specific outcome, the goal is to spot patterns that show how certain items or events tend to occur together. These...Blog
Anomaly detection is an unsupervised machine learning technique that identifies observations which differ significantly from most of the data. Unlike supervised methods such as classification or regression, anomaly detection does not need labelled outcomes. Instead,...Blog
Previously, we discussed about what feature extraction is and the algorithms that support it. In this post, the focus shifts to why feature extraction is so useful in real world machine learning scenarios. Drawing from Oracle Machine Learning documentation, feature...Blog
Machine learning projects are most successful when they follow a structured and repeatable process. Oracle Machine Learning adopts a well defined lifecycle that guides projects from the initial business problem through to deployment in a production environment. This...Blog
Previously the supported algorithms of the three main supervised machine learning techniques were covered. In this post, the supported algorithms of the unsupervised ML techniques will be covered. By definition, these algorithms analyse data without predefined labels...
