post-rfc
HLearn-algebra
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| post-rfc | HLearn-algebra | |
|---|---|---|
| 27 | 2 | |
| 2,187 | 1,619 | |
| - | - | |
| 2.3 | 0.0 | |
| 9 months ago | almost 8 years ago | |
| Haskell | ||
| Creative Commons Attribution 4.0 | BSD 3-clause "New" or "Revised" License |
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post-rfc
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Haskell in Production: Standard Chartered
That's what it's best for, but personally I use it for everything. If I ever get into low-level code I'll probably use Rust though.
You can confirm that parsers/tokenizers is ranked "best in class" here though:
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Recommendations for well informed, up-to-date guide to Haskell backend engineering
Note that this is ported from here: https://github.com/Gabriella439/post-rfc/blob/main/sotu.md which comes with more exposition.
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I want to learn Haskell, but...
State of the Haskell Ecosystem
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Why are haskell applications so obscure?
According to State of the Haskell ecosystem, Haskell is THE language of choice for implementing compilers, and THE language of choice for writing parsers. Thus, it is not surprising to see more Haskell projects from those particular categories than from other categories.
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base case
This is great for understanding what libraries to use in the Haskell ecosystem: https://github.com/Gabriella439/post-rfc/blob/main/sotu.md
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Haskell for beginners
In particular, I got comfortable reading hackage documentation to understand quickly how to use libraries (aeson, megaparsec, mtl, pipes, etc), got comfortable with the ecosystem (this helped: https://github.com/Gabriella439/post-rfc/blob/main/sotu.md), got comfortable with the main language idioms and features (https://smunix.github.io/dev.stephendiehl.com/hask/tutorial.pdf) and got comfortable with simple things that for some reason had confused me before (case, \case, let).
- What can I do in Haskell? UwU
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Is there "Are We <#$%&> Yet" type of websites for Haskell?
Gabriella Gonzalez has a great doc that is reasonably up-to-date, sounds similar to what you're looking for? https://github.com/Gabriella439/post-rfc/blob/main/sotu.md
- What I wish I had known about voice feminization from the beginning
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Haskell for Artificial Intelligence?
With that being said, Python is without a doubt the best option, and I'd also be very interested to read the articles you found that say that Python is not a good choice because it's been the industry standard for a long time now. Data science and machine learning are one of the areas where the Haskell ecosystem is not as strong as other languages, but libraries and tools do exist. There's a great list of Haskell resources by domain here, and as you can see, there are Haskell bindings to tensorflow and pytorch, along with other libraries that support common data science programming.
HLearn-algebra
- looking for simple regression (or classification) library
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Haskell for Artificial Intelligence?
GitHub - mikeizbicki/HLearn: Homomorphic machine learning
What are some alternatives?
ihp - 🔥 The fastest way to build type safe web apps. IHP is a new batteries-included web framework optimized for longterm productivity and programmer happiness
tensorflow - Haskell bindings for TensorFlow
envy - :angry: Environmentally friendly environment variables
fastbayes - A Haskell library for Bayesian modeling algorithms that are fast(er than general-purpose sampling).
hackage-server - Hackage-Server: A Haskell Package Repository
rc - Reservoir Computing, an RNN flavor
rlua - High level Lua bindings to Rust
haskell-ml - Various examples of machine learning, in Haskell.
awesome-haskell - A collection of awesome Haskell links, frameworks, libraries and software. Inspired by awesome projects line.
neural - Neural Nets in native Haskell
hoogle - Haskell API search engine
multilinear-io - Input/output capability in various formats (binary, CSV, JSON) for Multilinear package in Haskell.