Machine Learning Test and Evaluation (MLTE), available for download from GitHub, is a semi-automated process and infrastructure for testing ML models based on stakeholder-generated quality ...

Software testing, especially in large scale projects, is a time intensive process. The article explores optimizing test execution, saving machine resources, and reducing feedback time to developers.

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

An innovative strategy that analyzes specific regions of the genome offers the possibility of early diagnosis of schizophrenia, reports a team led by researchers at Baylor College of Medicine. The ...

Deepchecks says the only way to ensure high-quality machine learning models are regularly updated is to draw on the lessons learned from software development, and apply regular testing and validation.

In this article, let’s explore how machine learning is revolutionizing software testing and breaking new ground for QA teams and enterprises alike, as well as how to successfully implement it.

Blood samples collected from patients with severe COVID-19 can be analyzed by a machine learning approach to predict whether they will recover and survive or die from the disease, a PLOS Digital ...

With machine learning, we can reduce maintenance efforts and improve the quality of products. It can be used in various stages of the software testing life-cycle, including bug management, which is an ...

8,500 The number of machine learning models researchers trained to test the limits of deep learning 500,000 The number of unique molecules used to train the deep learning models.

He believes machine learning is key to handling increasing test volumes. “The quality of digital business is the quality of the code and testing that runs it.

There’s an art and science to picking machine learning and statistics-based models. Andrew Clark, cofounder and CTO of Monitaur, explains how to experiment with synthetic data generation.