by Gabriel Tam | Aug 10, 2026 | BTS Artificial Intelligence (AI), BTS Knowledge Hub
Large datasets can contain a huge amount of information, this does not always make analysis easier. In many cases, the challenge is finding a simpler way to represent the data while keeping the patterns that actually matter. Non Negative Matrix Factorization (NMF) is...
by Gabriel Tam | Aug 1, 2026 | BTS Artificial Intelligence (AI), BTS Knowledge Hub
Finding significant data groups within datasets can be a challenge, especially when there are no predefined categories to work with. O Cluster, short for Orthogonal Partitioning Clustering, is an unsupervised machine learning algorithm developed by Oracle to...
by Gabriel Tam | Jul 25, 2026 | BTS Artificial Intelligence (AI), BTS Knowledge Hub
Understanding text can be a difficult task for computers. While people can easily recognize the meaning behind words and phrases, computers need methods that assists them interpret language in a meaningful way. Explicit Semantic Analysis, also referred to as ESA, is a...
by Gabriel Tam | Jul 18, 2026 | BTS Artificial Intelligence (AI), BTS Knowledge Hub
Singular value decomposition is an unsupervised machine learning technique used primarily for feature extraction and the transformation of high dimensional data into a lower dimensional space whilst keeping meaningful data properties (dimensionality reduction). When...
by Gabriel Tam | Jul 11, 2026 | BTS Artificial Intelligence (AI), BTS Knowledge Hub
As datasets continue to grow in size and complexity, analyzing every variable can quickly become challenging. Many datasets contain hundreds or even thousands of features, some often provide similar information. Principal Component Analysis, also known as PCA, is an...
by Gabriel Tam | Jul 4, 2026 | BTS Artificial Intelligence (AI), BTS Knowledge Hub
When working with large amounts of data, one of the hardest challenges is not knowing where to start. Data can contain thousands to millions of records, and without clear labels, it can be difficult to understand how those records relate to one another. K-Means...
