Machine learning is even less predictable than other software development, and the training phase can take longer than you expect, because training is part of developing the system not part of ...

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

In machine learning, FPGA and eFPGA players are lining up for a piece of the inferencing market. All told, Linley estimates there will be 1.7 billion machine-learning client devices by 2022. “GPUs ...

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 ...

Some 87% of corporate projects do not get past the experiment phase and never make it into production. There's no need to reinvent the wheel, learn to program and then relearn statistics as though ...

Researchers have determined how to build reliable machine learning models that can understand complex equations in real-world situations while using far less training data than is normally expected.