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mitmath
18335
Jupyter Notebook2022–2025
mitmath / 18335

18335

18.335 - Introduction to Numerical Methods course

2Distinct people
2Mentions
0Explicit recommenders
599GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

18.335 - Introduction to Numerical Methods course

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 10:56:20 AM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year2 dated mentions

Observed mentions: 2022-01-08 13:27:34 UTC to 2025-12-26 01:54:47 UTC.

012022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20222023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments20232024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2025

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC101
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC000
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC000
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC101

What Hacker News says

1 sources
Math was always the stumbling block for me then I realized through work how easy it is with pure rational or reals except when you need to translate it to an algorithm now you are throwing out all the elegant linear algebra for a numerical representation and using obscure characteristic polynomial constructs just to run a program and now math sucks again I went back to the beginning. A nice course for this is of course TAOCP volume 2 old testament or MITs math github https://github.com/mitmath/18335/tree/spring22 (change the yr to suit) like we can't even have nice things like gradient descent anymore because it zigzags and is too inefficient
In Show HN: Exploring Mathematics with Python

MAKE YOURSELF AT HOME

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