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The Use Cases of Anomaly Detection in Oracle Machine Learning

BTS Sales Engagement Hub, Oracle Artificial Intelligence (AI)

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,...

The Use Cases of Feature Extraction in Oracle Machine Learning

BTS Sales Engagement Hub, Oracle Artificial Intelligence (AI)

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...

Oracle Machine Learning (ML) Process Summary

BTS Sales Engagement Hub, Oracle Artificial Intelligence (AI)

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...

Unsupervised Oracle Machine Learning (ML) Algorithms

BTS Sales Engagement Hub, Oracle Artificial Intelligence (AI)

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...

Supervised Oracle Machine Learning (ML) Algorithms

BTS Sales Engagement Hub, Oracle Artificial Intelligence (AI)

  An algorithm is a step-by-step procedure designed to perform a specific task or solve a certain problem. It involves a sequence of instructions that lead to the outcome. Supervised machine learning algorithms, on the other hand, are slightly different. These...
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