Machine learning (ML) is a subset of artificial intelligence (AI) that involves using algorithms and statistical models to enable computer systems to learn from data and improve performance on a ...

A recent study shows that 1 in 5 people use AI every day. From the chatbot helping you budget smarter to the recommendations ...

Imagine a future where quantum computers supercharge machine learning—training models in seconds, extracting insights from ...

Balance training patients may soon be able to get AI feedback during home exercises, with four wearable sensors and a new ...

eWeek content and product recommendations are editorially independent. We may make money when you click on links to our partners. Learn More Machine learning (ML) uses advanced mathematical models ...

Machine learning is powering most of the recent advancements in AI, including computer vision, natural language processing, predictive analytics, autonomous systems, and a wide range of applications.

From exploratory data analysis to automated machine learning, look to these techniques to get your data science project moving — and to build better models. Do you need to classify data or predict ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

As machine learning becomes more pervasive in the data center and the cloud there will be a need to share and aggregate information and knowledge but without exposing or moving the underlying data.

AI-powered systems have swept through business, surfing a rising wave of occasionally justified hype. When they're good, they're really good—take, for example, a neural net designed to help Japanese ...