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

    • Teknologi

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

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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