| 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. |
| 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. |
| Jack-Cherish/Machine-Learning |
6,628 |
|
0 |
0 |
over 3 years ago |
0 |
|
3 |
|
Python |
| :zap:机器学习实战（Python3）：kNN、决策树、贝叶斯、逻辑回归、SVM、线性回归、树回归 |
| biolab/orange3 |
4,469 |
|
57 |
47 |
about 2 years ago |
63 |
October 31, 2023 |
99 |
other |
Python |
| 🍊 :bar_chart: :bulb: Orange: Interactive data analysis |
| mljar/mljar-supervised |
2,867 |
|
0 |
2 |
about 2 years ago |
84 |
September 26, 2023 |
141 |
mit |
Python |
| Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation |
| parrt/dtreeviz |
2,720 |
|
2 |
22 |
over 2 years ago |
41 |
July 07, 2022 |
61 |
mit |
Jupyter Notebook |
| A python library for decision tree visualization and model interpretation. |
| tirthajyoti/Machine-Learning-with-Python |
2,712 |
|
0 |
0 |
almost 3 years ago |
0 |
|
8 |
bsd-2-clause |
Jupyter Notebook |
| Practice and tutorial-style notebooks covering wide variety of machine learning techniques |
| benedekrozemberczki/awesome-decision-tree-papers |
2,266 |
|
0 |
0 |
about 2 years ago |
0 |
|
1 |
cc0-1.0 |
Python |
| A collection of research papers on decision, classification and regression trees with implementations. |
| greyhatguy007/Machine-Learning-Specialization-Coursera |
2,082 |
|
0 |
0 |
over 2 years ago |
0 |
|
16 |
mit |
Jupyter Notebook |
| Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG |
| edyoda/data-science-complete-tutorial |
1,575 |
|
0 |
0 |
over 3 years ago |
0 |
|
12 |
|
Jupyter Notebook |
| For extensive instructor led learning |
