Want to get better performance with Python? Here's how to use NumPy to toe the 'invisible line' of data and memory transfers and optimize efficiency.

Give your Python applications a rocket boost—here's everything you need to know to get started with Cython and its Python-to-C compiler.

Python is perfectly capable for programmers with certain tasks in math and science fields, despite perceived Python performance issues vs. other languages.

Learn about some of the best Python libraries for programming Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL).

[Zoltán] sends in his very interesting implementation of a NumPy-like library for micropython called ulab. He had a project in MicroPython that needed a very fast FFT on a micro controller, and ...

Unlike R, Python has no clear “winning” IDE. We recommend Spyder because it is well-designed for scientific computing and the popular packages associated with this type of work (NumPy, SciPy, pandas, ...

Aspiring data-science and machine-learning developers now have more Microsoft-made free video tutorials to learn how to build software in Python, one of today's most popular and versatile ...

NumPy, the Python package for scientific computing, is an adolescent with prospects for a prolific maturity.

Scikits are Python-based scientific toolboxes built around SciPy, the Python library for scientific computing. Scikit-learn is an open source project focused on machine learning: classification ...