Submission timeline
2007–2026One slot for every year since HN launched. Height is that year's peak points; orange marks a 100+ point or 50+ comment breakout. Select a bar to open its strongest thread.
First comments on top threads
HN comment orderThis is a phenomenal example of how to teach math. You can go through theory, formulas and proofs all day long (yes, sometimes rigor is needed), but this type of teaching is sticky. It takes a lot more time to display information in the way the author has done, but it reaps massive benefits for those trying to learn. In my mind, math is about concepts and there is no reason why we can't start teaching math like this. Amazing…
For anyone interested in Markov chains (aimed at language) in Python, and their relationship to the larger world of language modeling (including "modern" RNNLMs and so on) this post by Yoav Goldberg is an excellent introduction, with clear and simple code [1]. Extending the Markov chain even a few steps can give really impressive generated results. Clone/download [2] if you want to run the code yourself. [1] http://nbviewer.jupyter.org/urls/gist.githubusercontent.com/... [2]…
The first top-level comment from each of the four biggest threads, in HN’s own order. Excerpts are shortened; open a comment for full context.
- Breakout years
- 2
- Total points
- 1202
- Total comments
- 112
100+ points or 50+ comments
reference only — not used in Hall rules or ranking
reference only — not used in Hall rules or ranking
Every submission
| Date | Title as submitted | By | Points | Comments |
|---|---|---|---|---|
| 2016-03-20 | Markov Chains Explained Visually (2014)First breakout | sonabinu | 419 | 44 |
| 2018-04-24 | Visual introduction to Markov Chains | platelminto | 2 | 0 |
| 2018-06-28 | Markov Chains Explained Visually | dvfjsdhgfv | 2 | 0 |
| 2018-08-15 | Markov Chains Explained Visually (2014)Best thread · Latest 20+ point return | aogl | 779 | 68 |