69 results found Sort:

3.9k
17.0k
mit
436
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 tas...
Created 2016-08-05
3,646 commits to master branch, last one a day ago
1.2k
8.2k
apache-2.0
190
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 computa...
Created 2017-07-18
49,096 commits to master branch, last one 15 hours ago
1.0k
5.0k
other
188
🍊 :bar_chart: :bulb: Orange: Interactive data analysis
Created 2013-02-22
15,556 commits to master branch, last one 4 days ago
Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
Created 2022-06-16
145 commits to main branch, last one 4 months ago
Practice and tutorial-style notebooks covering wide variety of machine learning techniques
Created 2017-07-17
502 commits to master branch, last one 2 years ago
337
3.0k
mit
46
A python library for decision tree visualization and model interpretation.
Created 2018-08-13
621 commits to master branch, last one 5 months ago
For extensive instructor led learning
Created 2018-09-15
155 commits to master branch, last one 2 years ago
112
672
apache-2.0
23
A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.
Created 2021-04-22
629 commits to main branch, last one 8 days ago
Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet
Created 2020-03-20
830 commits to master branch, last one 3 years ago
A library to train, evaluate, interpret, and productionize decision forest models such as Random Forest and Gradient Boosted Decision Trees.
Created 2021-04-22
1,071 commits to main branch, last one a day ago
14
476
agpl-3.0
5
Visualize decision trees in Python
Created 2024-07-24
120 commits to main branch, last one 29 days ago
101
471
mit
17
A Lightweight Decision Tree Framework supporting regular algorithms: ID3, C4.5, CART, CHAID and Regression Trees; some advanced techniques: Gradient Boosting, Random Forest and Adaboost w/categorical ...
Created 2019-03-06
404 commits to master branch, last one 3 months ago
75
434
mit
16
pure Go implementation of prediction part for GBRT (Gradient Boosting Regression Trees) models from popular frameworks
Created 2018-09-15
149 commits to master branch, last one about a year ago
🔥🌟《Machine Learning 格物志》: ML + DL + RL basic codes and notes by sklearn, PyTorch, TensorFlow, Keras & the most important, from scratch!💪 This repository is ALL You Need!
Created 2020-04-02
130 commits to master branch, last one about a year ago
33
393
mit
9
Compiler for LightGBM gradient-boosted trees, based on LLVM. Speeds up prediction by ≥10x.
Created 2021-04-27
292 commits to master branch, last one 2 months ago
58
380
unknown
18
Home repository for the Regularized Greedy Forest (RGF) library. It includes original implementation from the paper and multithreaded one written in C++, along with various language-specific wrappers.
Created 2016-06-08
484 commits to master branch, last one 3 years ago
A python library to build Model Trees with Linear Models at the leaves.
Created 2021-03-27
30 commits to main branch, last one 2 years ago
75
282
mit
23
Simple machine learning library / 簡單易用的機器學習套件
Created 2016-01-15
235 commits to master branch, last one 6 years ago
Machine Learning University: Decision Trees and Ensemble Methods
Created 2020-12-18
21 commits to main branch, last one about a year ago
Rubi for Mathematica
Created 2018-05-30
99 commits to master branch, last one 12 months ago
25
222
other
10
R package that makes basic data exploration radically simple (interactive data exploration, reproducible data science)
Created 2018-04-06
590 commits to master branch, last one 2 months ago
Machine learning beginner to Kaggle competitor in 30 days. Non-coders welcome. The program starts Monday, August 2, and lasts four weeks. It's designed for people who want to learn machine learning.
Created 2021-08-15
39 commits to main branch, last one 3 years ago