Lost amongst the hype and hyperbole surrounding machine learning today, especially deep learning, is the critical distinction between correlation and causation.

Sparse data is still representing something within the variables. Missing data, however, means that the data points are unknown. Challenges in machine learning with sparse data. There are several ...

A new study presents a machine learning model that accurately predicts the compressive strength of high-strength concrete, ...

Today’s data scientists and machine learning engineers now have a wide range of choices for how they build models to address the various patterns of AI for their particular needs.

Consider a machine learning model that classifies images. If your dataset is composed of 100×100-pixel images, then your problem space has 10,000 features, one per pixel.

Machine learning models are becoming increasingly important in the prediction of economic crises. The models, however, use datasets comprising a large number of predictors (features) which impairs ...

And we have not even touched upon Level 2 -- machine learning systems that incorporate new data and update in real-time. However, to come full circle, if Huyen's experience is anything to go by ...