The purpose of this repository is document the existing support for numerical computing and data science in the Haskell ecosystem.
NB: This effort has just begun, so there is precious little material so far. We will extend it over time and warmly welcome any contributions from the community. We are interested in original contributions in this repository (tutorials, API documentation, sample applications, etc). We are also interested in link collections to external resources on numerical computing and data science in the Haskell.
Tweag I/O is currently running a series of blog post that provides an overview over the array programming support in Haskell — with a focus on well maintained packages that have seen an uptake by the community.
- Array programming in Haskell — overview over the most widely used array packages
- Enter the matrix, Haskell style
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hmatrixprovides BLAS, LAPACK & GSL functionality in Haskell - Immutability and unboxing in array programming
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arrayprovides a basic array interface for boxed/unboxed and immutable/mutable arrays with generic indexing - Array fusion with vector
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vectorprovides collective operations for sequential, int-indexed boxed & unboxed arrays
| Project | Description |
|---|---|
| hmatrix | Matrix operations in Haskell |
| Frames | Data frames in Haskell |
| grenade | Deep learning |
| numerical | pre-alpha numerical package |
| ad | Automatic differentiation |
| jupyter | Notebook-style web app for working with data |
| haskell.do | Notebook-style web thing for Haskell |
| hakaru | Probabilistic programming |
Data Haskell: Open source community around doing data science in Haskell