MEmerqurio·Nov 15, 2017Submission
Thinc: Practical Machine Learning for NLP in Python
3 points · Open discussionexplosion
thinc
Python2017–2023
explosion / thinc
thinc
🔮 A refreshing functional take on deep learning, compatible with your favorite libraries
6Distinct people
11Mentions
0Explicit recommenders
2.9KGitHub stars
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🔮 A refreshing functional take on deep learning, compatible with your favorite libraries
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This week on Hacker News
Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 2:17:07 AM UTC.
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HN mentions by year11 dated mentions
Observed mentions: 2017-10-05 22:49:58 UTC to 2023-09-29 06:35:55 UTC.
Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.
View mention counts and date ranges
| Period | Start (UTC) | End (exclusive, UTC) | Mentions | Submissions | Comments |
|---|---|---|---|---|---|
| 2017 | 2017-01-01 00:00:00 UTC | 2018-01-01 00:00:00 UTC | 3 | 1 | 2 |
| 2018 | 2018-01-01 00:00:00 UTC | 2019-01-01 00:00:00 UTC | 2 | 0 | 2 |
| 2019 | 2019-01-01 00:00:00 UTC | 2020-01-01 00:00:00 UTC | 1 | 0 | 1 |
| 2020 | 2020-01-01 00:00:00 UTC | 2021-01-01 00:00:00 UTC | 3 | 1 | 2 |
| 2021 | 2021-01-01 00:00:00 UTC | 2022-01-01 00:00:00 UTC | 0 | 0 | 0 |
| 2022 | 2022-01-01 00:00:00 UTC | 2023-01-01 00:00:00 UTC | 1 | 0 | 1 |
| 2023 | 2023-01-01 00:00:00 UTC | 2024-01-01 00:00:00 UTC | 1 | 0 | 1 |
What Hacker News says
3 sourcesI did a linguistics degree before doing my computational linguistics PhD 2005-2010. In Australia we don't do any graduate coursework, so the last maths class I took was when I was 15 or 16. I'm now pretty good at these things. You can see my work here: https://explosion.ai
You might be interested in the machine learning library I wrote for spaCy: https://github.com/explosion/thinc . The backward propagation can be understood quite simply with callbacks.
The main problem I had, and I think you're having, is that the notation around calculus is just hopeless. It's even worse when you're trying to map between the equations and backpropagation, because what you need is slightly different. I also find the notations for functions really bad.
The other thing you need to get used to are the ways linear algebra overload the operators. This is just
Read the rest
data, not concepts. Personally I find it much easier to just work in the Einstein summation: https://obilaniu6266h16.wordpress.com/2016/02/04/einstein-su... . Once it's debugged, you can translate into faster calls to numpy.tensordot.
Don't go back to school. School's fucked. It'll take you three years to do about 200 hours of learning. Hiring a tutor would be vastly better if you need some help.
This is amazing -- we have a small mountain of Cython code, and almost everything is working out of the box!
Tests failing:
* https://github.com/explosion/spaCy
Confirmed working:
* https://github.com/explosion/thinc
* https://github.com/explosion/preshed
* https://github.com/explosion/cymem
* https://github.com/explosion/murmurhash
I doubt spaCy will ever be faster on PyPy (the neural network library Thinc is currently 50% slower). It'd still be really great to get it running, so people who benefit from PyPy for other parts of their stack don't have to manage two Python environments.
In PyPy v5.9 Released