As businesses increasingly rely on machine learning models to make informed decisions, the ability to develop accurate and reliable models is critical. However, in many industrial contexts, data annotation represents a ...

Principal component analysis (PCA) has been a commonly used unsupervised learning method with broad applications in both descriptive and inferential analytics. It is widely used for representation learning to extract key ...

In many industrial applications, obtaining labeled observations is not straightforward as it often requires the intervention of human experts or the use of expensive testing equipment. In these circumstances, active learning ...