| explosion/thinc |
2,774 |
|
569 |
67 |
about 2 years ago |
229 |
September 22, 2023 |
16 |
mit |
Python |
| 🔮 A refreshing functional take on deep learning, compatible with your favorite libraries |
| neohaskell/NeoHaskell |
246 |
|
0 |
0 |
over 2 years ago |
0 |
|
76 |
apache-2.0 |
|
| ⏩ NeoHaskell is a dialect of Haskell that is focused on newcomer-friendliness and productivity. |
| noahgift/functional_intro_to_python |
239 |
|
0 |
0 |
almost 5 years ago |
0 |
|
14 |
other |
Jupyter Notebook |
| [tutorial]A functional, Data Science focused introduction to Python |
| xebia-functional/xef |
153 |
|
1 |
15 |
about 2 years ago |
320 |
October 14, 2024 |
36 |
apache-2.0 |
Kotlin |
| Building applications with LLMs through composability, in Kotlin, Scala, ... |
| leopiney/tensor-safe |
96 |
|
0 |
0 |
about 5 years ago |
0 |
April 18, 2019 |
1 |
bsd-3-clause |
Haskell |
| A Haskell framework to define valid deep learning models and export them to other frameworks like TensorFlow JS or Keras. |
| suvojit-0x55aa/mixed-precision-pytorch |
46 |
|
0 |
0 |
over 6 years ago |
0 |
|
1 |
wtfpl |
Python |
| Training with FP16 weights in PyTorch |
| JohnNay/forecastVeg |
34 |
|
0 |
0 |
about 5 years ago |
0 |
|
1 |
other |
Python |
| A Machine Learning Approach to Forecasting Remotely Sensed Vegetation Health in Python |
| DataHaskell/awesome-haskell-ml |
18 |
|
0 |
0 |
over 8 years ago |
0 |
|
0 |
cc0-1.0 |
|
| 📚 - Resources for Machine Learning and Haskell |
| lettier/interactive-simple-linear-regression |
14 |
|
0 |
0 |
almost 9 years ago |
0 |
|
0 |
apache-2.0 |
PureScript |
| A PureScript, browser-based implementation of simple linear regression. |
| orionsbelt-battlegrounds/obb-rules |
13 |
|
1 |
0 |
almost 10 years ago |
31 |
October 05, 2015 |
8 |
epl-1.0 |
Clojure |
| Orion's Belt BattleGrounds battle engine |
