Developers are still using Python for data tasks and AI, but many are still using older releases, putting productivity at risk.

Python has turned into a data science and machine learning mainstay, while Julia was built from the ground up to do the job.

The core of the Python data model architecture is special methods (also known as "magic methods"). These methods, which start ...

The core of the Python data model architecture is the special methods (also known as 'magic methods'). These methods, which ...

Unlock automatic understanding of text data! Join our hands-on workshop to explore how Python—and spaCy in particular—helps you process, annotate, and analyze text. This workshop is ideal for data ...

Python should focus on the application areas where it's good and for the web that's the backend and for scientific data processing." ...

There are many reasons why Python has emerged as the number one language for data science. It’s easy to get started and relatively forgiving for beginners, yet it’s also powerful and extensible enough ...

Streaming data records are typically small, measured in mere kilobytes, but the stream often goes on and on without ever stopping. Streaming data, also called event stream processing, is usually ...

Integration of Python for data science, graph processing for NoSQL-like functionality, and it runs on Linux as well as Windows. At almost 30 years of age, Microsoft's flagship database has learned ...