This book is edited by Li Hui and Chen Yanyan, with associate editors Yang Yu, Gao Yong, Zhang Qiaosheng, Bi Ye, and Liu Dengzhi. It is rich in content, covering 32 theories and 32 practical cases, ...

Aspiring data-science and machine-learning developers now have more Microsoft-made free video tutorials to learn how to build software in Python, one of today's most popular and versatile ...

This online data science specialization is designed for learners with little to no programming experience who want to use Python as a tool to play with data. You will learn basic input and output ...

The language R is in the midst of a sizzling resurgence this summer. One might hypothesize that this growth is coming at the expense of Python, by far the dominant language for data science. But some ...

New extension pack bundles wildly popular tools for Python development, assisted by the AI-powered GitHub Copilot and a data wrangler.

Java has a lot going for it, but it's not the top language for data science. Java professionals may want to familiarize themselves with Python or R for data science workflows.

Students are constantly learning new analysis skills, and it can be easy to fall behind, get confused, or need a touch-up after a break from material. To help out, CADS has student interns devoted to ...

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 ...

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.