Top all-time · #13704
Teddy Koker
Personal blog · teddykoker.com · on HN as teddykokeraiprogramming
Teddy Koker's personal blog at teddykoker.com covers ai and programming. Since 2020, 5 different Hacker News readers have linked it 10 times, most often “Beating The Odds: Machine Learning For Horse Racing (2019)”. It is still writing: the last post was on 2026-02-10, and you can follow it by feed.
Too few sampled comments (1) to say how often HN recommends it.?
Why HN links it
Linked in a thread titled "How Distortion Works in Music", so the post appears to explain music distortion. The one comment discusses analog versus digital distortion but does not evaluate the post.
Summarised by Claude from a sample of 1 HN comments that link here. Each comment is marked recommending, critical or neutral (citing without judging); how this works.
Most-linked posts?
- Beating The Odds: Machine Learning For Horse Racing (2019)2 people · 2 mentions · first linked 2021-05-02
- Performers: The Kernel Trick, Random Fourier Features, and Attention2 people · 2 mentions · first linked 2020-12-29
- Deep Learning for Guitar Effect Emulation2 people · 2 mentions · first linked 2020-05-11
What Hacker News says?
A digital signal can't be as "flawed" as an analogue one. The analog synthesizers exploit these flaws to produce richer and more interesting sounds that you just can't get in the digital world as it's too deterministic and the attempts to randomize behavior are too "white-noisy", instead of natural occuring distortions. There's been some advancements using AI, though, to model these flaws organically, which sound pr…
Comment linking /2020/05/deep-learning-for-guitar-effect-emulation/
on “How Distortion Works in Music”Submitted Deep Learning for Guitar Effect Emulation as a story · 314 points
HN discussionYou can find Benter’s paper about the model here: https://www.gwern.net/docs/statistics/decision/1994-benter.p... About a year ago I read this and attempted to build a similar model (with more layers ;)) using data I scraped from Hong Kong Jockey Club’s website. Although I used much fewer features, it still produced profit in held-out races: https://teddykoker.com/2019/12/beating-the-odds-machine-lear... . Obviously…
Comment linking /2019/12/beating-the-odds-machine-learning-for-horse-racing/
on “A Gambler Who Cracked the Horse-Racing Code (2018)”Submitted Beating The Odds: Machine Learning For Horse Racing (2019) as a story · 2 points
HN discussionSubmitted Learning JAX by Learning to Learn as a story · 2 points
HN discussionSubmitted DataLoaders Explained: Building a Multi-Process Data Loader from Scratch as a story · 2 points
HN discussionSubmitted Performers: The Kernel Trick, Random Fourier Features, and Attention as a story · 2 points
HN discussionSubmitted Performers: The Kernel Trick, Random Fourier Features, and Attention as a story · 2 points
HN discussionSubmitted NLP from Scratch: Annotated Attention as a story · 2 points
HN discussionSubmitted Learning to Learn with Jax as a story · 1 points
HN discussion