Pydantic: This library enforces type constraints and validates data, making sure consistency and accuracy. It is essential for structuring data in your AI workflows.

Python data science essential: SciPy 1.7 Python users who want a fast and powerful math library can use NumPy, but NumPy by itself isn’t very task-focused.

In this article, we’ll introduce you to some of the libraries that have helped make Python the most popular language for data science in Stack Overflow’s 2016 developer poll.

This article rounds up some of the most valuable free data science courses offered by top institutions like Harvard, IBM, and ...

Python for Data Science Essential Training is one of the most popular data science courses at LinkedIn Learning. This is course 1 of 2. In this course, instructor Lillian Pierson takes you step by ...

A key part of CUDA-X AI is RAPIDS. RAPIDS is a suite of open-source software libraries for executing end-to-end data science and analytics pipelines entirely on GPUs. And a key part of RAPIDS is Dask.

It’s also possible to interface with Python code by way of the PyCall library, and even share data between Python and Julia. Julia supports metaprogramming.