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Max Halford

Personal blog · maxhalford.github.io/blog · on HN as Lemaxoxodataprogramming

Max Halford's personal blog at maxhalford.github.io covers data and programming. Since 2017, 16 different Hacker News readers have linked it 35 times, most often “Text classification with Python 3.14's ZSTD module”. It is still writing: the last post was on 2026-09-08, and you can follow it by feed.

Visit the blog
35mentions?
16HN people?
2017–2026first – last linked?
Links on Hacker News per year · peak 9 in 2023

Too few sampled comments (2) to say how often HN recommends it.?

Why HN links it

HN readers link Max Halford's blog posts on text classification with zstd and on segmenting comic book panels, both about practical machine learning techniques.

Summarised by Claude from a sample of 2 HN comments that link here. Each comment is marked recommending, critical or neutral (citing without judging); how this works.

Technical essays by Max Halford on data science, machine learning, Python, SQL, and software engineering.

The author on HN?

Lemaxoxo · 265 karma · member since 2018

https://maxhalford.github.io/bio/

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

Most-linked posts?

  1. Text classification with Python 3.14's ZSTD module
    4 people · 4 mentions · first linked 2026-02-06
  2. Dynamic On-Screen Keyboards
    2 people · 2 mentions · first linked 2022-09-30
  3. Measuring the Carbon Footprint of Pizzas
    2 people · 2 mentions · first linked 2023-06-27
  4. Comic Book Panel Segmentation
    2 people · 2 mentions · first linked 2022-03-09
  5. Text Classification by Data Compression
    2 people · 2 mentions · first linked 2021-06-08
  6. Answering “Why did the KPI change?” using decomposition
    2 people · 2 mentions · first linked 2023-08-15
  7. Do LLMs identify fonts?
    2 people · 2 mentions · first linked 2025-07-30
  8. Graph Components with DuckDB (2023)
    2 people · 2 mentions · first linked 2023-06-04

What Hacker News says?

  1. networked · 2026-09-22Recommends
    Check out "Text classification with Python 3.14's zstd module" ( https://maxhalford.github.io/blog/text-classification-zstd/ , https://news.ycombinator.com/item?id=46942864 ). I wanted to link it somewhere in the comments. :-)

    Comment linking /blog/text-classification-zstd/

    on “Can gzip be a language model?”
  2. Submitted Text Classification by Data Compression as a story · 105 points

    HN discussion
  3. matroid · 2024-02-27Recommends
    The original blog post by Max Halford ( https://maxhalford.github.io/blog/comic-book-panel-segmentat... ) does exactly that. I love his approach because, unlike mine, it is simple, yet it goes a long way. I'd encourage you to check it out. Can you explain what you mean by motion comic generation? Sounds interesting!

    Comment linking /blog/comic-book-panel-segmentation/

    on “Segmenting comic book frames”
  4. Submitted Do LLMs identify fonts? as a story · 64 points

    HN discussion
  5. Nice! I wrote about something similar for rectangular layouts: https://maxhalford.github.io/blog/dynamic-on-screen-keyboard...

    Comment linking /blog/dynamic-on-screen-keyboards/

    on “Markov Keyboard: keyboard layout that changes by Markov frequency (2019)”
  6. Submitted Stochastic gradient descent written in SQL as a story · 19 points

    HN discussion
  7. https://maxhalford.github.io/

    Comment linking /

    on “Ask HN: Could you share your personal website here?”
  8. Submitted Do LLMs Identify Fonts? as a story · 8 points

    HN discussion
  9. Cheers! Mainly a couple of things: - I don't like to have to put { { ref('source') }} everywhere. I think the tool should parse dependencies automatically. I wrote more about this here: https://maxhalford.github.io/blog/dbt-ref-rant/ - I don't like the idea each .sql file has to have an associated .yml file. It feels better to have everything in one place. For instance, with lea you can add a @UNIQUE tag as an SQL c…

    Comment linking /blog/dbt-ref-rant/

    on “Lea: Minimalist Alternative to Dbt”
  10. Submitted Text classification with Python 3.14's ZSTD module as a story · 5 points

    HN discussion
  11. Submitted Fuzzy Regex Matching in Python as a story · 3 points

    HN discussion
  12. Submitted A smooth approach to putting machine learning into production as a story · 3 points

    HN discussion
  13. Submitted Unknown pleasures with JavaScript as a story · 3 points

    HN discussion
  14. Submitted A brief guide to French polling data as a story · 2 points

    HN discussion
  15. Submitted Pub Quiz Flashcards as a story · 2 points

    HN discussion
  16. Submitted Graph Components with DuckDB (2023) as a story · 2 points

    HN discussion
  17. Submitted Answering “Why did the KPI change?” using decomposition as a story · 2 points

    HN discussion
  18. Submitted Text Classification by Data Compression as a story · 2 points

    HN discussion
  19. Submitted Graph Components with DuckDB as a story · 2 points

    HN discussion
  20. Submitted Comic Book Panel Segmentation as a story · 2 points

    HN discussion
  21. Submitted I got plagiarized and Google didn't help as a story · 2 points

    HN discussion
  22. Submitted Koza: Symbolic Regression Based Machine Learning in Golang as a story · 2 points

    HN discussion
  23. Submitted My unvarnished guide to solution engineering as a story · 1 points

    HN discussion
  24. Submitted Lower your warehouse costs via DuckDB transpilation as a story · 1 points

    HN discussion
  25. Submitted Text classification with Python 3.14's ZSTD module • Max Halford as a story · 1 points

    HN discussion
  26. Submitted Text classification with Python 3.14's ZSTD module as a story · 1 points

    HN discussion
  27. Submitted OCR spelling correction is hard as a story · 1 points

    HN discussion
  28. Submitted Answering “Why did the KPI change?” using decomposition as a story · 1 points

    HN discussion
  29. Submitted Measuring the Carbon Footprint of Pizzas as a story · 1 points

    HN discussion
  30. Submitted Measuring the Carbon Footprint of Pizzas as a story · 1 points

    HN discussion

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