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...Blog
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...Blog
For years, organisations have treated transformation as something you do and then move on from. A programme is launched. A roadmap is approved. Consultants arrive. Systems go live. A transformation banner is quietly taken down. And yet, only months later, many leaders...
