From deepfakes to natural language processing and more, the open source world is ripe with projects to support software development on the frontiers of artificial intelligence and machine learning.

The world’s leading tech companies open-source their projects on GitHub by releasing the code behind their popular algorithms. Technology is advancing rapidly, and computational costs are lower than ...

Google has opened up the source code of two machine learning (ML) on-device systems, MobileNetV3 and MobileNetEdgeTPU, to the open source community.

The first step to a successful ML project is to understand that these projects require different processes, terminology, workflows, and tools than those needed by traditional development.

The go-to for data scientists seeking huge datasets. Thousands of datasets span themes from AI to finance to health, and they are free!

Although Python is the widely recognized de facto, go-to programming language for machine learning and many other artificial intelligence projects, a new study shows C# is holding its own in the space ...

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

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.

In summary AI and ML projects will fail without good data because data is the foundation that enables these technologies to learn. Data strategies and AI and ML strategies are intertwined.