In the analysis of big data sets, the first step is usually the identification of "features" -- data points with particular predictive power or analytic utility. Choosing features usually requires ...

Most go off course. To make sure yours succeed, consider these five steps. by Iavor Bojinov When I worked as a data scientist at LinkedIn in 2018 and 2019, AI was of interest only to a small team of ...

In recent years, JupyterLab has rapidly become the tool of choice for data scientists, machine learning (ML) practitioners, and analysts worldwide. This powerful, web-based integrated development ...

Overview: Statistical analysts turn varied datasets into clear insights that support decisions across sectors.Strong skills ...

Spreadsheets are still useful, but if you do a lot of work with numbers, you'll realize that they have limitations.

Still using Excel for your data analysis? Learn how to leverage Python so you can work with larger datasets and automate repetitive tasks. Learning to code, whether with Python, JavaScript, or another ...

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 ...