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

In membership inference attacks, the adversary can work back from the machine learning algorithm to discover the training data used.

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 ...

If you’re just learning how to build models or are creating a simple prototype with a relatively small set of training data, you’re more likely to want to use a PC.

Drenik: How important is quality data in machine learning initiatives, especially in healthcare? Konam: Quality data is essential to train deployable machine learning models in healthcare.

One short week ago, I called on governments to use existing data and proven machine learning and AI techniques to help healthcare systems combat the COVID-19 pandemic.

Data science, machine learning and artificial intelligence are key enabling capabilities in today's business world but few executives know how to deploy them effectively.

Ways to detect a poisoned machine learning dataset The good news is that organizations can take several measures to secure training data, verify dataset integrity and monitor for anomalies to ...

Organizations are turning to machine learning because of the return on investment. The ones doing it in real-time are topping the charts.