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Daniel Nouri

Personal blog · danielnouri.org/notes · on HN as dnouriaiprogramming

Daniel Nouri's personal blog at danielnouri.org covers ai and programming. Since 2011, 9 different Hacker News readers have linked it 12 times, most often “Deep learning tutorial: using convolutional nets to detect facial keypoints”. It is still writing: the last post was on 2026-08-25, and you can follow it by feed.

Visit the blog
12mentions?
9HN people?
2011–2026first – last linked?
Links on Hacker News per year · peak 3 in 2014

Too few sampled comments (4) to say how often HN recommends it.?

Why HN links it

HN readers link Daniel Nouri's pages on SuperCollider streams and patterns, and his tutorial on convolutional neural networks for deep learning. Comments mostly cite them as references.

Summarised by Claude from a sample of 4 HN comments that link here. Each comment is marked recommending, critical or neutral (citing without judging); how this works.

Writing about Python, machine learning, teaching, and international affairs.

The author on HN?

dnouri · 93 karma · member since 2012

http://danielnouri.org

From their public HN profile, which links to this site.

Most-linked posts?

  1. Deep learning tutorial: using convolutional nets to detect facial keypoints
    3 people · 3 mentions · first linked 2014-12-17
  2. Pyramid is too damn easy - a success story
    2 people · 2 mentions · first linked 2011-04-26
  3. Using deep learning to listen for whales
    2 people · 2 mentions · first linked 2014-01-10

What Hacker News says?

  1. I was first introduced to the concept of 'streams' akin to this in SuperCollider, which uses them as building blocks for musical patterns. http://danielnouri.org/docs/SuperColliderHelp/Streams-Patter... http://danielnouri.org/docs/SuperColliderHelp/Streams-Patter... SuperCollider is a fun language to study. You end up with compositional structures like the following (notice 'inf', which indicates an infinite loop) P…

    Comment linking /docs/SuperColliderHelp/Streams-Patterns-Events/Pattern.html

    on “Introducing a new data structure, streams, in Javascript”
  2. Submitted Using deep learning to listen for whales as a story · 80 points

    HN discussion
  3. Great write up - make that a rough draft for your post. I was going to edit my comment earlier to point out that coroutine is not generator. I realized this limitation one day while trying to do it in python. You cannot just yield another stream. SuperCollider has proper co-routines: http://danielnouri.org/docs/SuperColliderHelp/Core/Kernel/Ro... and the pattern library is built entirely around embedding in streams…

    Comment linking /docs/SuperColliderHelp/Core/Kernel/Routine.html

    on “Why C++ for Unreal 4”
  4. Submitted Pyramid is too damn easy - a success story as a story · 6 points

    HN discussion
  5. Is there a similar tutorial or resource that shows how to do face detection (not recognition) using deep learning. I came across tutorial from kaggle [1] but I'm looking for something that uses ML to detect where the faces are in an image. [1] - http://danielnouri.org/notes/2014/12/17/using-convolutional-...

    Comment linking /notes/2014/12/17/using-convolutional-neural-nets-to-detect-facial-keypoints-tutorial/

    on “Unsupervised Feature Learning and Deep Learning Tutorial”
  6. Submitted Deep learning tutorial: using convolutional nets to detect facial keypoints as a story · 5 points

    HN discussion
  7. onnoonno · 2015-08-04Recommends
    This one is very helpful, too: http://danielnouri.org/notes/2014/12/17/using-convolutional-...

    Comment linking /notes/2014/12/17/using-convolutional-neural-nets-to-detect-facial-keypoints-tutorial/

    on “Faster deep learning with GPUs and Theano”
  8. Submitted Modern Python CI with Coverage in 2025 as a story · 3 points

    HN discussion
  9. Submitted Using Deep Learning to Listen for Whales as a story · 2 points

    HN discussion
  10. Submitted Pyramid is too damn easy - a success story as a story · 2 points

    HN discussion
  11. Submitted The minimal case for a minimal subagents implementation in Pi as a story · 1 points

    HN discussion

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