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datanecdote

HN member
Joined
Wed, Aug 12, 2020, 7:47 PM UTC
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24 items

About datanecdote

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Recent public activity

  1. comment
    Comment #24843917

    As the document I linked to says, Jax autograd supports custom data types and custom gradients. It’s honestly exhausting arguing with all you Julia boosters. You can down vote me t…

  2. comment
    Comment #24843632

    Try reading the docs before making sweeping negative comments about what a piece of software can and cannot do. https://jax.readthedocs.io/en/latest/notebooks/autodiff_cook...

  3. comment
    Comment #24843306

    It is true that Jax cannot differentiate through C code. But it can differentiate through python code that was written to accept Numpy.

  4. comment
    Comment #24843139

    For Jax I believe this is false. Jax is composable. In fact it’s a core design goal. Jax arrays implement the Numpy API. I routinely drop Jax arrays into other python libraries des…

  5. comment
    Comment #24842739

    How does Jax lose composability or introspection?

  6. comment
    Comment #24841185

    Lengthy, nuanced discussion about benchmarking between Turing devs and Stan devs.

  7. comment
    Comment #24840815

    The right benchmark is Stan https://github.com/TuringLang/TuringExamples/pull/25

  8. comment
    Comment #24840748

    When I look at google trends or redmonk rankings, Julia appears stable, not accelerating.

  9. comment
    Comment #24762871

    Why minizinc instead of Google OR? Seems like Google OR best minizinc at their own contest? https://www.minizinc.org/challenge2020/results2020.html Is it more customizable? Or expr…

  10. comment
    Comment #24750426

    Thanks Viral. To be clear, I’m a python user who’s cheering for Julia, because I live the problems of python and do see the potential of Julia as a better path. But unfortunately I…

  11. comment
    Comment #24748533

    > 2. I don't entirely follow this point. Perhaps using PyArrow's parser would be faster than what is timed here, but is that what the typical Python data science user would do? I a…

  12. comment
    Comment #24730729

    @Sukera Fair, but, if I break up all the loops and if statements into functions, those functions still have “end”s

  13. comment
    Comment #24730466

    That was mostly meant as a joke, thus the “;-)” I don’t really care much about syntax choices, but my small complaint about “end” is that it takes up a line which reduces the amoun…

  14. comment
    Comment #24730113

    Thanks. I watched the JuliaCon state of Julia presentation. As I wrote in my original post, I appreciate the investments the Julia core developers are making, that have improved bu…

  15. comment
    Comment #24729694

    Preach, brother. I’m cautiously optimistic that JAX (or something like JAX) can save the python programming language from stagnation by essentially building a feature-complete reim…

  16. comment
    Comment #24729471

    Let me second GP’s sentiment. I find Julia really slow for my purposes. I don’t know his reasoning, but I will explain mine. None of this is surprising and is oft discussed. Julia …

  17. comment
    Comment #24515194

    FWIW I agree with you. I’ve always found cython easier than Numba. And more performant. I think Numba has a lot of potential and will improve as they fill out remaining language co…

  18. comment
    Comment #24502271

    In the uncommon event I need to write a loop from scratch, and I need it to be really fast, I just rewrite that one jupyter cell in cython or numba. But that is a small piece of my…

  19. comment
    Comment #24499705

    Honest question from a heavy python user who would switch if it made sense: Are there any comprehensive benchmarks that show Julia outperforming Pandas or PyTorch or SciKit? Obviou…

  20. comment
    Comment #24300544

    I’m fascinated by Julia and have test driven it before but it didn’t click for me. Maybe I was doing it wrong and/or the ecosystem has matured since I last looked. I guess I genera…

  21. comment
    Comment #24300509

    Thanks for the pointers, those crates seem great. The flaky multithreading libs are my least favorite part of python, and rust’s strength in this area seems very appealing.

  22. comment
    Comment #24300489

    I deal with a lot of ragged data that is hard to vectorize, and currently write cython kernels when the inner loops take too long. Sounds like Rust might be faster than cython? Tha…

  23. comment
    Comment #24296999

    I am in similar boat. Python centric data scientist. Very tempted to try to learn Rust so I can accelerate certain ETL tasks. Question for Rust experts: On what ETL tasks would you…

  24. comment
    Comment #24136137

    Worth keeping in mind the principal agent problem literature. Selling equity in a company is vulnerable to “lemon” problems. Startups with product market fit want to minimize dilut…