HLearn-algebra
dex-lang
| HLearn-algebra | dex-lang | |
|---|---|---|
| 2 | 25 | |
| 1,619 | 1,538 | |
| - | 0.5% | |
| 0.0 | 8.8 | |
| almost 8 years ago | 6 days ago | |
| Haskell | Haskell | |
| BSD 3-clause "New" or "Revised" License | BSD 3-clause "New" or "Revised" License |
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.
HLearn-algebra
- looking for simple regression (or classification) library
-
Haskell for Artificial Intelligence?
GitHub - mikeizbicki/HLearn: Homomorphic machine learning
dex-lang
-
Thinking in an Array Language
A really nice approach to this I've seen recently is Google's research on [Dex](https://github.com/google-research/dex-lang).
- Function Composition in Programming Languages – Conor Hoekstra – CppNorth 2023 [video]
- Dex Lang: Research language for array processing in the Haskell/ML family
-
[D] Have their been any attempts to create a programming language specifically for machine learning?
Dex
-
[D] PyTorch 2.0 Announcement
Have you tried Dex? https://github.com/google-research/dex-lang It is in a relatively early stage, but it is exploring some interesting parts of the design space.
- Mangle, a programming language for deductive database programming
-
Looking for languages that combine algebraic effects with parallel execution
I think [Dex](https://github.com/google-research/dex-lang) might be along the lines of what you're looking for, although its focus is on SIMD GPU-style parallelism rather than thread-level parallelism.
-
“Why I still recommend Julia”
Dex proves indexing correctness without a full dependent type system, including loops.
See: https://github.com/google-research/dex-lang/pull/969
-
Haskell for Artificial Intelligence?
In case you want to see one research direction that's combining practical machine learning and functional programming, one of the authors of JAX (and the main author of its predecessor, Autograd) is writing Dex (https://github.com/google-research/dex-lang), a functional language for array processing. The compiler itself is written in Haskell. JAX is one of the most popular libraries for doing a lot of machine learning these days, along with Tensorflow and PyTorch. You might also want to see the bug in the JAX repo about adding Haskell support, for some context: https://github.com/google/jax/issues/185
What are some alternatives?
tensorflow - Haskell bindings for TensorFlow
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
fastbayes - A Haskell library for Bayesian modeling algorithms that are fast(er than general-purpose sampling).
futhark - :boom::computer::boom: A data-parallel functional programming language
rc - Reservoir Computing, an RNN flavor
julia - The Julia Programming Language
haskell-ml - Various examples of machine learning, in Haskell.
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
neural - Neural Nets in native Haskell
hasktorch - Tensors and neural networks in Haskell
multilinear-io - Input/output capability in various formats (binary, CSV, JSON) for Multilinear package in Haskell.
CIPs