Netflix's data-science team has open-sourced its Metaflow Python library, a key part of the 'human-centered' machine-learning infrastructure it uses for building and deploying data-science workflows.

Overview PyCharm, DataSpell, and VS Code offer strong features for large projects.JupyterLab and Google Colab simplify data ...

These simple operations and others are why NumPy is a building block for statistical analysis with Python. NumPy also makes ...

Already using NumPy, Pandas, and Scikit-learn? Here are seven more powerful data wrangling tools that deserve a place in your ...

A lot of software developers are drawn to Python due to its vast collection of open-source libraries. Lately, there have been a lot of libraries cropping up in the realm of Machine Learning (ML) and ...

This sponsored post covers how Intel Performance Libraries are working to ramp up python performance. Surprise! Python* is now the most popular programming language, according to IEEE Spectrum’s fifth ...

But data science is a specific field, so while Python is emerging as the most popular language in the world, R still has its place and has advantages for those doing data analysis. Hoping to settle ...

SciPy, Numba, Cython, Dask, Vaex, and Intel SDC all have new versions that aid big data analytics and machine learning projects. If you want to master, or even just use, data analysis, Python is the ...

Java can handle large workloads, and even if it hits limitations, peripheral JVM languages such as Scala and Kotlin can pick up the slack. But in the world of data science, Java isn't always the go-to ...

What are some use cases for which it would be beneficial to use Haskell, rather than R or Python, in data science? originally appeared on Quora: the place to gain and share knowledge, empowering ...