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josephmisiti
awesome-machine-learning
Python2014–2026
josephmisiti / awesome-machine-learning

awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

AI & Machine LearningLearning & ReferenceLibraries & SDKs
Explore on GitHubRead Hacker News discussions
17Distinct people
18Mentions
0Explicit recommenders
74.8KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

A curated list of awesome Machine Learning frameworks, libraries and software.

GitHub

Where it is used

No documented product use was verified in the last source check.

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

Mentioned in the same Hacker News threads. That is not proof they are substitutes.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 9:01:12 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 year18 dated mentions

Observed mentions: 2014-07-16 01:44:29 UTC to 2026-09-22 00:30:04 UTC.

012342014-01-01 00:00:00 UTC to 2015-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments20142015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 4 mentions; 1 submissions, 3 comments2016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 4 mentions; 1 submissions, 3 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 2 mentions; 2 submissions, 0 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments20202021-01-01 00:00:00 UTC to 2022-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2022-01-01 00:00:00 UTC to 2023-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2023-01-01 00:00:00 UTC to 2024-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2024-01-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2025-01-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2026-01-01 00:00:00 UTC to 2027-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments. Incomplete calendar period.2026*

* An incomplete calendar period is marked with an outlined bar. Its count is not directly comparable with a full period.

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
20142014-01-01 00:00:00 UTC2015-01-01 00:00:00 UTC110
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC413
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC110
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC413
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC220
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC000
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC211
20212021-01-01 00:00:00 UTC2022-01-01 00:00:00 UTC000
20222022-01-01 00:00:00 UTC2023-01-01 00:00:00 UTC000
20232023-01-01 00:00:00 UTC2024-01-01 00:00:00 UTC101
20242024-01-01 00:00:00 UTC2025-01-01 00:00:00 UTC101
20252025-01-01 00:00:00 UTC2026-01-01 00:00:00 UTC110
2026 (partial)2026-01-01 00:00:00 UTC2027-01-01 00:00:00 UTC101

What Hacker News says

2 sources
rkeulemans·May 5, 2020Submission

Ask HN: Crowd-sourced educational resources recommendations?

As a college student (MSc Computer Science) I often encounter the situation that I am sitting in lectures that suck. The content is very interesting, but it is presented in a very bad or boring way. Most professors are not really interested in providing the best education possible (they want to do research) and therefore their performance and material (and recommended books, papers etc.) are moderate at best [0]. As a solution I head out to YouTube [1, 2], Goodreads, HN threads [3], GitHub pages [4,5] and MOOCs, Medium posts, Google [6] etc. to find alternative material to learn from. While there are some indications of quality/learnability (comment sentiment, ratings) it is still hard to judge which material is best. I want to find the material that best suits my learning needs so I can learn more efficient and effective (and thus more).
Read the rest
I was wondering whether a crowd computing platform (for learners, by learners) could help to collaboratively select and judge material. After searching for a topic there is some sort of rating (up/down votes) and difficulty classification {easy, intermediate, expert} to help you easily find the material that suits you best as a learner. Material can be anything from books, lectures, papers, webpages to complete MOOCs and pages of universities offering their courses for free [8]. Any thoughts on this? [0] - https://www.ratemyprofessors.com/ [1] - https://www.youtube.com/user/eaterbc/ [2] - https://www.youtube.com/playlist?list=PLD63A284B7615313A [3] - https://news.ycombinator.com/item?id=15398550 [4] - https://github.com/josephmisiti/awesome-machine-learning/blob/master/books.md [5] - https://github.com/ossu/computer-science [6] - https://seeing-theory.brown.edu/ [7] - https://www.acm.org/binaries/content/assets/education/cs2013_web_final.pdf [8] - https://stanford.edu/~shervine/teaching/cs-229/refresher-probabilities-statistics
1 points · Open discussion

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