| chasedehan/BoostARoota |
139 |
|
0 |
2 |
about 8 years ago |
5 |
January 22, 2018 |
3 |
mit |
Python |
| A fast xgboost feature selection algorithm |
| rambler-digital-solutions/criteo-1tb-benchmark |
117 |
|
0 |
0 |
almost 9 years ago |
0 |
|
4 |
|
Jupyter Notebook |
| Benchmark of different ML algorithms on Criteo 1TB dataset |
| IntelPython/scikit-learn_bench |
99 |
|
0 |
0 |
over 2 years ago |
0 |
|
18 |
apache-2.0 |
Python |
| scikit-learn_bench benchmarks various implementations of machine learning algorithms across data analytics frameworks. It currently support the scikit-learn, DAAL4PY, cuML, and XGBoost frameworks for commonly used machine learning algorithms. |
| bukosabino/btctrading |
83 |
|
0 |
0 |
almost 8 years ago |
0 |
|
2 |
mit |
Jupyter Notebook |
| Time Series Forecast with Bitcoin value, to detect upward/down trends with Machine Learning Algorithms |
| gmontamat/gentun |
80 |
|
0 |
0 |
over 2 years ago |
0 |
|
12 |
apache-2.0 |
Python |
| Hyperparameter tuning for machine learning models using a distributed genetic algorithm |
| vlazovskiy/route-optimizer-machine-learning |
58 |
|
0 |
0 |
about 7 years ago |
0 |
|
0 |
|
Jupyter Notebook |
| Route optimization solution which uses evolutionary algorithm with XGBoost model to optimize travel times. |
| davpinto/ml-simulations |
28 |
|
0 |
0 |
over 9 years ago |
0 |
|
0 |
|
R |
| Animated Visualizations of Popular Machine Learning Algorithms |
| nuanio/xgboost-node |
25 |
|
0 |
2 |
over 8 years ago |
7 |
August 16, 2019 |
2 |
other |
Cuda |
| Run XGBoost model and make predictions in Node.js |
| arnaudvl/ml-parameter-optimization |
21 |
|
0 |
0 |
about 8 years ago |
0 |
|
1 |
mit |
Python |
| Hyperparameter optimization for machine learning algorithms. |
| xiecong/Simple-Implementation-of-ML-Algorithms |
17 |
|
0 |
0 |
over 2 years ago |
0 |
|
0 |
mit |
Python |
| My simplest implementations of common ML algorithms |
