TrainCheck uses training invariants to find the root cause of hard-to-detect errors before they cause downstream problems, ...

Despite the AI hype, tools are proving valuable for leading-edge chip manufacturing. More aggressive feature scaling and ...

AutoML for Embedded is available now on Visual Studio Code Marketplace and GitHub.

By automating the end-to-end machine learning pipeline, it empowers less-experienced developers to build high-quality models ...

Federated Learning (FL) is a decentralized machine learning (ML) approach where multiple clients collaboratively train a shared model over several update rounds without exchanging local data. Similar ...

Machine learning helps improve accuracy and efficiency of small-molecule calculations Microsoft researchers used deep learning to create new DFT model by Sam Lemonick, special to C&EN June 20, 2025 ...

One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing.

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...

Typical Azure Machine Learning Project Lifecycle (source: Microsoft). At the upcoming Visual Studio Live! @ Microsoft HQ 2025 conference in Redmond, Eric D. Boyd, founder and CEO of responsiveX, will ...

By combining fine-tuning and in-context learning, you get LLMs that can learn tasks that would be too difficult or expensive for either method ...