Machine learning’s impact on technology is significant, but it’s crucial to acknowledge the common issues of insufficient training and testing data.

Machine learning systems operate in a data-driven programming domain where their behaviour depends on the data used for training and testing. This unique characteristic underscores the importance of ...

To make the most of machine learning you have to train your models right. Here's how to get reliable results from your data.

Machine learning (ML)-based approaches to system development employ a fundamentally different style of programming than historically used in computer science. This approach uses example data to train ...

Training, Validating, and Testing EC Recurrence Models Only variables included in models that were superior to an AUC >0.8 in phase I were brought forward to the second phase of analysis.

Intel’s Nidhi Chappell, head of machine learning, reveals what separates the two computer sciences and why they're so important ...

Machine learning is hot. Where it applies, it heatedly enables data-rich and knowledge-lean automation of valuable tasks of perception, classification and numeric prediction. Its sibling, machine ...