applied-fp-course
Applied Functional Programming Course - Move from exercises to a working app! (by qfpl)
haskell-ml
Various examples of machine learning, in Haskell. (by capn-freako)
applied-fp-course | haskell-ml | |
---|---|---|
6 | 1 | |
621 | 20 | |
0.5% | - | |
1.6 | 1.8 | |
6 months ago | about 2 years ago | |
Haskell | Haskell | |
GNU General Public License v3.0 or later | BSD 3-clause "New" or "Revised" License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
applied-fp-course
Posts with mentions or reviews of applied-fp-course.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-05-08.
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Are you interested in a 'Haskell in depth' reading group?
Yes. Also interested in working through Sandy Maguire's Algebra-Driven Design and https://github.com/qfpl/applied-fp-course if anyone else is interested.
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Next Step After Haskell Programming from First Principles
I would suggest the QFPL's "Applied FP Course": https://github.com/qfpl/applied-fp-course (disclaimer: I helped write it).
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So I've finished _Hask ell Programming from First Principles_. What's next?
Have a crack at https://github.com/qfpl/applied-fp-course , which takes you through building a small HTTP API from barebones wai upward, using realistic coding patterns. I helped write it so I'm a bit biased, but I think it's good. When QFPL ran the course in-person, students would get so engrossed that we'd have to drag them away from their computers otherwise they'd miss out on the free lunches. That means it does something right.
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What are some ways I could tickle my (beginner) haskell-brain with something *useful*?
Applied course: https://github.com/qfpl/applied-fp-course
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Exercise/Practice Resources for Beginners / Intermediate
Once you're through those, you might want to give https://github.com/qfpl/applied-fp-course a try.
haskell-ml
Posts with mentions or reviews of haskell-ml.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-12-04.
What are some alternatives?
When comparing applied-fp-course and haskell-ml you can also consider the following projects:
milewski-ctfp-pdf - Bartosz Milewski's 'Category Theory for Programmers' unofficial PDF and LaTeX source
tensorflow - Haskell bindings for TensorFlow
adventofcode - Advent of Code solutions of 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022 and 2023 in Scala
HLearn-algebra - Homomorphic machine learning
c-scikit-learn - C bindings for scikit-learn
rc - Reservoir Computing, an RNN flavor
backprop - Heterogeneous automatic differentiation ("backpropagation") in Haskell
order-statistics - L-estimators and order statistics
haskell-wushu-panda - Haskell in practice course
htvm - Haskell experiments involving TVM AI framework
neural - Neural Nets in native Haskell
genetics - A Genetic Algorithm library in Haskell
applied-fp-course vs milewski-ctfp-pdf
haskell-ml vs tensorflow
applied-fp-course vs adventofcode
haskell-ml vs HLearn-algebra
applied-fp-course vs c-scikit-learn
haskell-ml vs rc
applied-fp-course vs backprop
haskell-ml vs order-statistics
applied-fp-course vs haskell-wushu-panda
haskell-ml vs htvm
haskell-ml vs neural
haskell-ml vs genetics