Live data from Hacker News

Viewing profile — kootenpv

kootenpv

HN member
Joined
Sun, Aug 14, 2016, 5:02 PM UTC
HN karma
147
Public activity
33 items

About kootenpv

No profile information was provided.

Recent public activity

  1. comment
    Comment #37638167

    On phone I typed with a capital letter the correct word but it was considered wrong.

  2. comment
    Comment #31838246

    I have 2 popular python projects, one with 4.9k and one with 2.3k stars and I don't qualify :/ https://github.com/kootenpv If anyone knows why pls let me know

  3. comment
    Comment #21750599

    Models are cached and not large so the setup time is very low. I'll time it when I get to a PC

  4. comment
    Comment #21741481

    Perfect interview questions to get to the juice details haha! The problem is that choice of compression is very much dependent on the sample size, so this is why just choosing the …

  5. comment
    Comment #21741387

    Yea, I thought parameters per compression algorithm should indeed be added in a next version :) more compute but definitely an improvement. I think pandas doesn't offer zstd as opt…

  6. comment
    Comment #21741383

    Yea zstd is really amazing... if I would choose a single one all the time it'd be zstd for sure.

  7. comment
    Comment #21738867

    I can give you this... the larger the data the more useful parquet and compression on it will be...

  8. comment
    Comment #21738487

    Yea I am aware of meta hyperparameter approach for ML, except they only focus on accuracy instead of also including train/prediction times in to the equation :) That's what I was r…

  9. comment
    Comment #21738242

    Yea, look at jekyll in combination with github pages. You can see my blog for example ( https://vks.ai ), the code is hosted here: https://github.com/kootenpv/kootenpv.github.io

  10. comment
    Comment #21738232

    There's TimescaleDB built on top of PostgreSQL.

  11. comment
    Comment #21738227

    Indeed, but this is for lossless compression :)

  12. comment
    Comment #21737987

    Spot on (I briefly touch on this in the article)! This is why I try to work with cheap-to-compute features. I used to calculate how unique all values were, but ended up taking a sa…

  13. comment
    Comment #21737962

    Yea - that is related to genetic programming. That, and using auto-encoders for e.g. image compression are known approaches in "AI". I'm particularly proud of this meta approach an…

  14. comment
    Comment #21737928

    I like mine for the fact that it is static and hosted on github pages with a not too bad design. https://vks.ai/

  15. comment
    Comment #21737911

    shrynk is not doing any compression itself, it's using ML to do a "meta" approach: it computes features on your data like how many rows, how many columns, how much duplication etc,…

  16. comment
    Comment #21737835

    I'm a long time fan of your blog :O

  17. comment
    Comment #21737817

    Definitely! I really optimized for "no development time spent" and was just using pandas to extract html tables into csv and just store them :-). 2 lines of code really. I had no i…

  18. story
  19. story
    IRL Silicon Valley TV-Show: Using Machine Learning to Compress – Shrynk

    Having caught up with the recent episodes I was laughing at the similarity with the TV-show Silicon Valley :) I'll explain the reason why I made the shrynk library. It began when m…

  20. comment
    Comment #21326783

    Privacy & Personal Analytics I am working on an open-source implementation that is based on the fundamental idea of privacy. The consumers should have full control eventually. For …

  21. story
  22. story
  23. comment
    Comment #20140061

    I'm happy to share with you the result of this project, it certainly has been a lot of fun! First of all it was shocking how many messages we had over such a long time (more than 3…

  24. story
  25. comment
    Comment #14773750

    The best article I have read in a long time.