Creating smart, accurate AI algorithms is an ongoing effort that requires validation of training sets and some level of human intervention. Here's a guide to how to craft effective ones.

As usual in machine learning, there's no completely standard terminology. In this article, the data used to determine when to stop training is called the validation data, and the data used to estimate ...

Machine learning models are trained with huge amounts of data and must be tested before practical use. For this, the data must first be divided into a larger training set and a smaller test set ...

Materials and Methods Data were collected from two French prospective multicenter cohorts of patients with cancer 70 years and older, referred for GA: ELCAPA (training set January 2007-March 2016) and ...

Thousands of images—including identifiable faces—were found in a small subset of DataComp CommonPool, a major AI training set for image generation scraped from the web.