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The Use Cases of Feature Extraction in Oracle Machine Learning

The Use Cases of Feature Extraction in Oracle Machine Learning

by Gabriel Tam | Feb 21, 2026 | BTS Artificial Intelligence (AI), BTS Knowledge Hub

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

Oracle Machine Learning (ML) Process Summary

by Gabriel Tam | Feb 14, 2026 | BTS Artificial Intelligence (AI), BTS Knowledge Hub

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

Unsupervised Oracle Machine Learning (ML) Algorithms

by Gabriel Tam | Feb 7, 2026 | BTS Knowledge Hub, BTS 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 analyze data without predefined labels...
Supervised Oracle Machine Learning (ML) Algorithms

Supervised Oracle Machine Learning (ML) Algorithms

by Gabriel Tam | Jan 31, 2026 | BTS Artificial Intelligence (AI), BTS Knowledge Hub

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 are, by...

Unsupervised Machine Learning Techniques

by Gabriel Tam | Jun 2, 2024 | BTS Artificial Intelligence (AI), BTS Knowledge Hub

Unsupervised learning is a type of machine learning technique that involves training a model on an unlabeled dataset. The aim is to discover hidden patterns or groupings in the data without pre-established labels. There are four types of unsupervised Oracle machine...
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