THE VIDEO SHELF · scientific python history
Travis Oliphant: NumPy, SciPy, Anaconda, Python & Scientific Programming | Lex Fridman Podcast #224
Lex Fridman interviews Travis Oliphant, creator of NumPy, SciPy and Anaconda, about scientific Python and its history. It runs about three hours.
Why HN readers recommended it
Recommended as a firsthand history of how Python became the language of scientific computing and ML.
This is a summary from the source dataset, not an endorsement by Hacker News or the video creator.
Video & recommendation details
- Creator / channel
- Lex Fridman
- Topic
- scientific python history
- Format
- podcast
- Level
- intermediate
- HN recommenders in dataset
- 2
- HN mentions in dataset
- 4
- Recommendation years in dataset
- 2021–2024
These counts and years describe the included Hacker News records; they are not YouTube views or the video’s publication date.
From the original HN conversations
Excerpts from the recorded comments. Follow each source for the full comment and surrounding discussion.
Yup, I agree that Python composes like Unix does, which is a reason for its phenomenal growth: Narrow Waists Can Be Interior or Exterior: PyObject vs. Unix Files - [LINK] The appendix links to: Why is Python the language of machine learning? [LINK] In particular, …
chubot on Hacker News · 2024-04
In Autoconf makes me think we stopped evolving too soonBecause Python has NumPy, which implements vectorized math on arrays and matrices. Machine learning algorithms are implemented naturally and efficiently with those primitives. PyTorch, TensorFlow, and I think every other machine learning framework in Python all use NumPy. JavaScript, Ruby, and Perl either don't have …
chubot on Hacker News · 2021-11
In Ask HN: How did Python become the lingua franca of ML/AI?This episode of the lex fridman podcast gives a good overview of how python's scientific computing community developed. [VIDEO]
calmdown13 on Hacker News · 2022-03
In The counterintuitive rise of Python in scientific computing (2020)
Summaries, classifications and recommendation records are from the HackerTube source dataset. Read about this library and its limitations.