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Top 18 Haskell Machine Learning Projects
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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tensor-safe
A Haskell framework to define valid deep learning models and export them to other frameworks like TensorFlow JS or Keras.
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HashedExpression
Type-safe modelling DSL, symbolic transformation, and code generation for solving optimization problems.
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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fastbayes
A Haskell library for Bayesian modeling algorithms that are fast(er than general-purpose sampling).
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multilinear-io
Input/output capability in various formats (binary, CSV, JSON) for Multilinear package in Haskell.
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- Haskell deep learning tutorials [Blog]
- looking for simple regression (or classification) library
- Why Hypergraphs? (2013)
- Haskell for Artificial Intelligence?
- Rank 3 Stencils for "Efficient Parallel Stencil Convolution in Haskell" (Repa)
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Index
What are some of the best open-source Machine Learning projects in Haskell? This list will help you:
Project | Stars | |
---|---|---|
1 | HLearn-algebra | 1,619 |
2 | tensorflow | 1,563 |
3 | grenade | 1,438 |
4 | neural | 122 |
5 | tensor-safe | 101 |
6 | openai-hs | 45 |
7 | HashedExpression | 42 |
8 | htvm | 21 |
9 | haskell-ml | 19 |
10 | icicle | 18 |
11 | fastbayes | 11 |
12 | xgboost-haskell | 8 |
13 | hmep | 7 |
14 | rc | 7 |
15 | order-statistics | 6 |
16 | multilinear | 5 |
17 | ngram | 3 |
18 | multilinear-io | 1 |
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