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fastai
numerical-linear-algebra
Jupyter Notebook2017–2021
fastai / numerical-linear-algebra

numerical-linear-algebra

Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course

6Distinct people
7Mentions
0Explicit recommenders
11KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra 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 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM 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 year7 dated mentions

Observed mentions: 2017-07-23 14:55:33 UTC to 2021-08-13 19:38:36 UTC.

01232017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20172018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20192020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 3 mentions; 1 submissions, 2 comments2021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2021

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
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC101
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC101
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC101
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC312
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC101

What Hacker News says

7 sources
https://github.com/topics/linear-algebra?l=jupyter+notebook lists "Computational Linear Algebra for Coders" https://github.com/fastai/numerical-linear-algebra "site:GitHub.com inurl:awesome linear algebra jupyter" lists a few awesome lists with interactive linear algebra resources: https://www.google.com/search?q=site%3Agithub.com+inurl%3Aaw... 3blue1brown's "Essence of linear algebra" playlist has some excellent tutorials with intuition-building visualizations built with manim: https://youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFit... https://github.com/ManimCommunity/manim
In Interactive Linear Algebra (2019)
Surprised (and delighted!) to see this pop up on the front page of HN today! This course is designed to teach proficient coders the practice of deep learning, that is: how to train accurate models; how to test and debug models; and key deep learning concepts. It covers applications in vision, natural language processing, tabular data, and recommendation systems. If you're interested in diving deeper into the papers and math behind the scenes, as well as coding from the lowest levels (right down to the compiler level), you'll be interested in "Deep Learning from the Foundations", which is coming out in 2 weeks. The last two lessons are co-taught with Chris Lattner (creator of Swift, LLVM, and Clang). If you want to understand the underlying linear algebra implementation details, have a look at "Computational Linear Algebra for Coders": htt
Read the rest
ps://github.com/fastai/numerical-linear-algebra If you want to learn about decision trees, random forests, linear regression, validation sets, etc, try "Introduction to Machine Learning for Coders": https://course18.fast.ai/ml (All are free and have no ads. They are provided as a service to the community.) Let me know if you have any questions!
In Practical Deep Learning for Coders

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