#224 – Travis Oliphant: NumPy, SciPy, Anaconda, Python & Scientific Programming

#224 – Travis Oliphant: NumPy, SciPy, Anaconda, Python & Scientific Programming

Travis Oliphant is a data scientist, entrepreneur, and creator of NumPy, SciPy, and Anaconda. Please support this podcast by checking out our sponsors:
Novo: https://banknovo.com/lex
Allform: https://allform.com/lex to get 20% off
Onnit: https://lexfridman.com/onnit to get up to 10% off
Athletic Greens: https://athleticgreens.com/lex and use code LEX to get 1 month of fish oil
Blinkist: https://blinkist.com/lex and use code LEX to get 25% off premium

EPISODE LINKS:
Travis’s Twitter: https://twitter.com/teoliphant
Travis’s Wiki Page: https://en.wikipedia.org/wiki/Travis_Oliphant
NumPy: https://numpy.org/
SciPy: https://scipy.org/about.html
Anaconda: https://www.anaconda.com/products/individual
Quansight: https://www.quansight.com

PODCAST INFO:
Podcast website: https://lexfridman.com/podcast
Apple Podcasts: https://apple.co/2lwqZIr
Spotify: https://spoti.fi/2nEwCF8
RSS: https://lexfridman.com/feed/podcast/
YouTube Full Episodes: https://youtube.com/lexfridman
YouTube Clips: https://youtube.com/lexclips

SUPPORT & CONNECT:
– Check out the sponsors above, it’s the best way to support this podcast
– Support on Patreon: https://www.patreon.com/lexfridman
– Twitter: https://twitter.com/lexfridman
– Instagram: https://www.instagram.com/lexfridman
– LinkedIn: https://www.linkedin.com/in/lexfridman
– Facebook: https://www.facebook.com/lexfridman
– Medium: https://medium.com/@lexfridman

OUTLINE:
Here’s the timestamps for the episode. On some podcast players you should be able to click the timestamp to jump to that time.
(00:00) – Introduction
(07:06) – Early programming
(28:47) – SciPy
(45:41) – Open source
(57:23) – NumPy
(1:34:39) – Guido van Rossum
(1:46:57) – Efficiency
(1:55:49) – Objects
(2:02:47) – Numba
(2:11:53) – Anaconda
(2:16:20) – Conda
(2:31:56) – Quansight Labs
(2:35:32) – OpenTeams
(2:43:05) – GitHub
(2:48:35) – Marketing
(2:53:13) – Great programming
(3:04:03) – Hiring
(3:08:01) – Advice for young people

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