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, ...

Programming languages Python and R are often pitted against each other over which is best for data science and analysis. Both are popular, although Python appears to be much more widely used, at ...

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 ...

Not necessarily for the data-science and machine-learning communities built around Python extensions like NumPy and SciPy, but as a general programming language.

Data queries written in Python, a commonly used programming language, can grind data analytics platforms to a crawl, but a new platform may finally solve the Python efficiency problem.

Threading in Python by Reuven M. Lerner: threads can provide concurrency, even if they're not truly parallel. Using Python for Science by Joey Bernard: introducing Anaconda, a Python distribution for ...

As programming languages go, there’s no denying that Python is hot. Originally created as a general-purpose scripting language, Python somehow became the most popular language for data science. But is ...