| dmlc/xgboost |
25,253 |
|
796 |
972 |
about 2 years ago |
79 |
November 13, 2023 |
412 |
apache-2.0 |
C++ |
| Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow |
| microsoft/LightGBM |
15,819 |
|
278 |
574 |
about 2 years ago |
34 |
September 12, 2023 |
345 |
mit |
C++ |
| A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. |
| EthicalML/awesome-production-machine-learning |
15,344 |
|
0 |
0 |
about 2 years ago |
0 |
|
15 |
mit |
|
| A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning |
| catboost/catboost |
7,564 |
|
0 |
12 |
about 2 years ago |
20 |
September 19, 2023 |
539 |
apache-2.0 |
Python |
| A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU. |
| scikit-optimize/scikit-optimize |
2,700 |
|
80 |
191 |
about 2 years ago |
19 |
October 12, 2021 |
320 |
bsd-3-clause |
Python |
| Sequential model-based optimization with a `scipy.optimize` interface |
| stanfordmlgroup/ngboost |
1,543 |
|
0 |
14 |
about 2 years ago |
27 |
November 01, 2023 |
47 |
apache-2.0 |
Python |
| Natural Gradient Boosting for Probabilistic Prediction |
| HuwCampbell/grenade |
1,430 |
|
3 |
0 |
over 2 years ago |
1 |
April 12, 2017 |
23 |
bsd-2-clause |
Haskell |
| Deep Learning in Haskell |
| FluxML/Zygote.jl |
1,415 |
|
0 |
0 |
about 2 years ago |
0 |
|
418 |
other |
Julia |
| 21st century AD |
| EnzymeAD/Enzyme |
1,100 |
|
0 |
0 |
about 2 years ago |
0 |
|
137 |
other |
LLVM |
| High-performance automatic differentiation of LLVM and MLIR. |
| SimonBlanke/Gradient-Free-Optimizers |
1,072 |
|
0 |
7 |
over 2 years ago |
45 |
December 29, 2022 |
7 |
mit |
Python |
| Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces. |
