Basic Libraries for Data Science These are the basic libraries that transform Python from a general purpose programming language into a powerful and robust tool for data analysis and visualization.

Python's data operations, with libraries like NumPy, pandas, Seaborn, and Pingouin, are much more efficient when working with large amounts of data.

Anaconda today announced support for Snowflake Notebooks, an interactive, cell-based data science notebook similar to Jupyter. The move will let data scientists, data analysts, and data engineers ...

The Intel Distribution of Python, a repackaging of Continuum Analytics’s Anaconda distribution, incorporated MKL support to give Python data science and machine learning packages a boost.

Python and many of its popular data science and machine learning packages/libraries, such as NumPy and TensorFlow, are open source projects.

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

Python, Julia, and Rust are three leading languages for data science, but each has different strengths. Here's what you need to know.

Python According to a recent survey by KDNuggets, Python is the undisputed leader in use for data science and machine learning.

Python for Data Science Essential Training is one of the most popular data science courses at LinkedIn Learning. This is course 1 of 2.

Data science is perhaps the most exciting area in all of enterprise technology right now, and it’s evolving at a lightning pace.