Already using NumPy, Pandas, and Scikit-learn? Here are five more powerful Python data science tools that deserve a place in your toolkit.

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.

Data science and machine learning professionals have driven adoption of the Python programming language, but data science and machine learning are still lacking key tools in business and has room ...

The 10 hottest data science and machine learning tools include Databricks Mosaic AI, Dataiku, PyTorch and TensorFlow.

Positron is Posit's new, free IDE for data science. Users can work with Python and R. It explicitly does not replace RStudio.

Neptyne, a startup building a Python-powered spreadsheet platform, has raised $2 million in a pre-seed venture round.

Python was not built specifically for data science workloads, but it does include many features that make it easy to code against data science workloads such as read-eval-print loops, notebooks and ...

With organizations increasingly turning to data science to derive business value, the tools that support the work are proliferating. Here are the key tools successful data scientists rely on.

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.