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Dragan Djuric

Personal blog · dragan.rocks/articlesprogrammingdatascience

Dragan Djuric's personal blog at dragan.rocks covers programming, data and science. Since 2016, 30 different Hacker News readers have linked it 211 times, most often “Deep Diamond: Deep Learning in Clojure Is Fast, and Simpler Than Keras”. It is still writing: the last post was on 2025-12-09, and you can follow it by feed.

Visit the blog
211mentions?
30HN people?
2016–2025first – last linked?
Links on Hacker News per year · peak 60 in 2019

Dragan Djuric's Clojure Blog, Artificial Intelligence, Deep Learning, Bayesian Data Analysis, CUDA, GPU, OpenCL, Functional Programming, Probabilistic Programming, Data Science.

Most-linked posts?

  1. Deep Diamond: Deep Learning in Clojure Is Fast, and Simpler Than Keras
    4 people · 8 mentions · first linked 2020-09-05
  2. LU Factorization and Linear Systems for Programers
    4 people · 5 mentions · first linked 2017-09-07
  3. /
    4 people · 5 mentions · first linked 2019-03-08
  4. Use Matrices Efficiently in Clojure
    4 people · 5 mentions · first linked 2017-06-26
  5. Fast Vector Broadcasting in Java, CPU and CUDA (2018)
    3 people · 4 mentions · first linked 2018-07-25
  6. Interactive GPU Programming, Part 1: Hello CUDA
    3 people · 4 mentions · first linked 2018-01-17
  7. Billions of Random Numbers in a Blink of an Eye
    3 people · 4 mentions · first linked 2019-06-12
  8. Interactive GPU Programming, Part 3: CUDA Context Shenanigans
    3 people · 3 mentions · first linked 2018-03-01
  9. Clojure is not afraid of the GPU [Slides]
    3 people · 3 mentions · first linked 2016-10-20
  10. /
    2 people · 11 mentions · first linked 2019-06-09

What Hacker News says?

  1. I currently publish a series of detailed articles that cover exactly that. https://dragan.rocks/articles/19/Deep-Learning-in-Clojure-Fr...

    Comment linking /articles/19/Deep-Learning-in-Clojure-From-Scratch-to-GPU-0-Why-Bother

    on “Implementing a Neural Network from Scratch in Python”
  2. Submitted Clojure Linear Algebra Refresher: Eigenvalues and Eigenvectors as a story · 206 points

    HN discussion
  3. Also, there are a few presentations availavle at http://dragan.rocks . just follow the blog posts.

    Comment linking /

    on “Prophet: forecasting at scale”
  4. Submitted Interactive GPU Programming, Part 1: Hello CUDA as a story · 179 points

    HN discussion
  5. I recently published a series of 16 blog posts Deep Learning from Scratch to GPU that does exactly that! [0] I also started working on a book titled "Deep Learning for Programmers"[1] that takes it even further! You can subscribe today and start reading the drafts as they are written. [0] https://dragan.rocks [1] https://aiprobook.com

    Comment linking /

    on “Practical Deep Learning for Coders”
  6. Submitted CUDA 10 in Clojure as a story · 157 points

    HN discussion
  7. In my experience, it works just fine. Clojure for the frontend is the best-in-class frontend dev environment that I've worked with. Instant hot code reloading, a browser-connected repl, great debugging tools, and a really nice collection of libraries for getting stuff done. I've never had to use native APIs for iOS and Android, so I can't speak to that from experience, but I know that there's some really nice machin…

    Comment linking /

    on “PureOS is convergent”
  8. Submitted Interactive GPU Programming, Part 2: Hello OpenCL as a story · 142 points

    HN discussion
  9. May I plug-in with ClojureCUDA, a high-level library that lets you write CUDA with almost no overhead, but write it in the interactive Clojure REPL. https://github.com/uncomplicate/clojurecuda There's also tons of free tutorials at https://dragan.rocks And a few books! (not free) at https://aiprobook.com Everything from scratch, interactive, line-by-line, and each line is executed in the live REPL.

    Comment linking /

    on “Introduction to CUDA programming for Python developers”
  10. Submitted Clojure Linear Algebra Refresher: 1 – Vector Spaces as a story · 142 points

    HN discussion
  11. I would think Clojure vs. Java would be used given immutability. I like both Haskell and Racket for math, especially this article on geometric algebra with Haskell: https://crypto.stanford.edu/~blynn/haskell/ga.html I am personally learning Shen[1] because Lisp, optional typing (great type system), and the formal work done within it, and for it in proving, verification and other related endeavors. It seems to tick t…

    Comment linking /

    on “Translating math into code with examples in Java, Racket, Haskell, Python (2011)”
  12. Submitted Foundations of ML and AI: Book recommendations as a story · 134 points

    HN discussion
  13. (My own writings) Deep Learning from Scratch to GPU at https://dragan.rocks Deep Learning for Programmers (book in progress) at https://aiprobook.com/deep-learning-for-programmers

    Comment linking /

    on “New Fast.ai Course: A Code-First Introduction to Natural Language Processing”
  14. Submitted LU Factorization and Linear Systems for Programers as a story · 131 points

    HN discussion
  15. You might find my Clojure Linear Algebra Refresher helpful. http://dragan.rocks/articles/17/Clojure-Linear-Algebra-Refre... This is the link for the first part. You'll find further articles there. It walks you through the code, explain things briefly, and points you to the exact places in a good Linear Algebra with Application textbook where this is explained in detail.

    Comment linking /articles/17/Clojure-Linear-Algebra-Refresher-Vector-Spaces

    on “Linear Algebra for AI”
  16. Submitted Fast Tensors in Clojure – A Sneak Peek as a story · 122 points

    HN discussion
  17. Let me chip in with some self-promotion. This book explains and executes every single line of code interactively, from low level operations to high-level networks that do everything automatically. The code is built on the state of the art performance operations of oneDNN (Intel, CPU) and cuDNN (CUDA, GPU). Very concise readable and understandable by humans. https://aiprobook.com/deep-learning-for-programmers/ Here's…

    Comment linking /

    on “What I wish someone had told me about tensor computation libraries”
  18. Submitted CuPy Accelerates NumPy on the GPU? Hold My Cider, Here's Clojure as a story · 120 points

    HN discussion
  19. > It's not Clojure-dead It never ceases to amaze me. Almost every single time, whenever there's a post or a comment on HN that mentions Clojure or Clojurescript, there's always someone from outside of the Clojure community attacking the language, saying things that are simply untrue. Like people are afraid of it becoming too successful. It's not some zero-sum game - the success of one language ecosystem doesn't mean…

    Comment linking /

    on “What's Next for Scala”
  20. Submitted Deep Learning in Clojure from Scratch to GPU: Learning a Regression as a story · 120 points

    HN discussion
  21. https://dragan.rocks and also the Downloads section of the https://aiprobook.com

    Comment linking /

    on “Numerical Linear Algebra for Programmers”
  22. Submitted Clojure from Scratch to GPU: A Simple Neural Network Training API as a story · 120 points

    HN discussion
  23. The follow up article addresses this concern. Similar results https://dragan.rocks/articles/20/Clojure-Numpy-Cupy-CPU-GPU-...

    Comment linking /articles/20/Clojure-Numpy-Cupy-CPU-GPU-2

    on “Numerical Linear Algebra for Programmers”
  24. Submitted Singular Value Decomposition for Programmers as a story · 119 points

    HN discussion
  25. The book looks interesting and the associated libraries (neanderthal for e.g.) But while going through your performance comparison [1], I feel something is off. I am not that familiar with libpython-clj and how it works, but looks like you are loading python from within the JVM and in turn the python is loading the C++/fortran OpenBLAS libraries to get the numerical calculations done for the Correlation Coefficient.…

    Comment linking /articles/20/Clojure-Numpy-Cupy-CPU-GPU

    on “Numerical Linear Algebra for Programmers”
  26. Submitted Clojure Numerics: Orthogonalization and Least Squares as a story · 118 points

    HN discussion
  27. Oh, so many things. The parallelism isn't actually that powerful, and in 2019 there's very little to set it apart. The building blocks are great, e.g. immutability everywhere, but few of the built-in primitives are actually usable (hidden unconfigurable thread pools etc). Stack traces still regularly horrible. Libraries are regularly abandoned. ClojureScript integrating with npm etc is more stress than you'd like. C…

    Comment linking /

    on “Why I Switched from Python to Clojure (2016)”
  28. Submitted Deep Learning from Scratch to GPU: CUDA and OpenCL as a story · 110 points

    HN discussion
  29. There is also part 1 of this tutorial: http://dragan.rocks/articles/17/Clojure-Linear-Algebra-Refre...

    Comment linking /articles/17/Clojure-Linear-Algebra-Refresher-Vector-Spaces

    on “Clojure Linear Algebra Refresher: Eigenvalues and Eigenvectors”
  30. Submitted Deep Learning on the GPU in Clojure from Scratch: Sharing Memory as a story · 105 points

    HN discussion

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