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.

Libraries are collections of shared code. They're common in Python, where they're also called "modules," but they're also ...

Python is the most popular programming language, outranking C and C++. Enterprises are using Python for HPC with the help of Intel Performance Libraries.

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

Nvidia wants to extend the success of the GPU beyond graphics and deep learning to the full data science experience. Open source Python library Dask is the key to this.

In addition to supporting Python, the company is supporting things like the Juypter data science notebook, the Streamlit framework, and the Bokeh visualization library, Bajuk says.

But with Python libraries, data solutions can be built much faster and with more reliability. SciKit-Learn, for example, has built-in algorithms for classification, regression, clustering, and ...

What are some use cases for which it would be beneficial to use Haskell, rather than R or Python, in data science? This question was originally answered on Quora by Tikhon Jelvis.