"With hundreds of millions of downloads per month, NumPy simplifies and standardizes the treatment of complex numeric arrays, enabling mathematical computations that are necessary to do science - including artificial intelligence (AI) - in the Python language. This is one reason why Python has become the go-to language of scientific computing. As a 2020 Nature research article pointed out , "NumPy underpins almost every Python library that does scientific or numerical computation, which includes SciPy but also Matplotlib, pandas, scikit-learn and scikit-image.""
"SciPy, in turn, is a collection of scientific algorithms, many of which Oliphant created. Now a technology entrepreneur and chief AI scientist at OpenTeams in Austin, Texas, Oliphant has gone from scientist to software developer to chief executive to venture capitalist - all thanks to NumPy, he says. "NumPy has been a driving force for my whole life." Now, his career has taken him to the silver screen."
In 2005 Travis Oliphant was an information scientist working on medical and biological imaging at Brigham Young University when he began work on NumPy, a library that became central to scientific computing in Python. He first encountered Python as a graduate student in 1998 and found it readable and extensible. He developed NumPy and contributed to SciPy, standardizing complex numeric array handling and enabling mathematical computations necessary for science and AI. NumPy enjoys hundreds of millions of downloads per month and underpins nearly every Python scientific or numerical library. Oliphant later became a technology entrepreneur and chief AI scientist at OpenTeams, crediting NumPy for shaping his career.
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