Machine-learning algorithms use statistics to find patterns in massive* amounts of data. And data, here, encompasses a lot of things—numbers, words, images, clicks, what have you.

Machine learning is a branch of artificial intelligence that includes methods, or algorithms, for automatically creating models from data. Unlike a system that performs a task by following ...

Machine learning can help with claims in a number of ways. In addition, multiple ML tools can be used throughout the claims process. Take the First Notice of Loss (FNOL), the initial notification ...

The data lakehouse architecture is leading this change—particularly for machine learning (ML) and advanced analytics—by combining the strengths of both data lakes and data warehouses. The ...

Data lakes were built for big data and batch processing, but AI and machine learning models need more flow and third party connections. Enter the data hub concept that'll likely pick up steam.

The FDAP stack brings enhanced data processing capabilities to large volumes of data. Apache Arrow acts as a cross-language development platform for in-memory data, facilitating efficient data ...

Machine learning algorithms need data, so the researchers designed a polymerization process that would quickly and efficiently generate experimental data to feed into the mathematical model.