I searched and prototyped for low-code and no-code platforms that would enable technology teams to spike and experiment with machine learning capabilities. I focused mainly on low-code application ...

Machine learning, concluded: Did the “no-code” tools beat manual analysis? In the finale of our experiment, we look at how the low/no-code tools performed.

The complexity and size of software systems has increased to the extent that traditional manual development and maintenance ...

Suvendu Mohanty changed from software to ML engineering before the AI boom. Here's how he made the switch — and his advice ...

A big challenge in neuroscience is understanding how the brain encodes information. Neural networks are turning out to be great code crackers.

Automated machine learning promises to speed up the process of developing AI models and make the technology more accessible.

Excel has many features that allow you to create machine learning models directly within your workbooks.

Switzerland-based machine learning code review startup DeepCode — which bills itself as “Grammarly for coders” — has been acquired by Snyk, a post-unicorn valuation cybersecurity startup ...

As no-code AI has matured, it has also become valuable to seasoned data scientists and machine learning engineers, who are interested in automating the tedious parts of their job.

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

DirectML has been popular; it’s made it a lot easier for game developers to add machine learning features to their code, and it’s supported scientific computing applications that have been ...