71 results found Sort:

3.9k
17.2k
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
3,655 commits to master branch, last one 8 hours ago
1.2k
8.4k
apache-2.0
189
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
49,387 commits to master branch, last one 19 hours ago
1.1k
5.1k
other
185
🍊 :bar_chart: :bulb: Orange: Interactive data analysis
Created 2013-02-22
15,580 commits to master branch, last one 19 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 6 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
340
3.0k
mit
45
A python library for decision tree visualization and model interpretation.
Created 2018-08-13
622 commits to master branch, last one about a month ago
For extensive instructor led learning
Created 2018-09-15
155 commits to master branch, last one 2 years ago
113
679
apache-2.0
22
A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras.
Created 2021-04-22
640 commits to main branch, last one 14 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
1,124 commits to main branch, last one a day ago
17
491
agpl-3.0
6
Visualize decision trees in Python
Created 2024-07-24
121 commits to main branch, last one about a month ago
101
475
mit
16
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
405 commits to master branch, last one 24 days ago
76
439
mit
15
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
33
414
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 4 months 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
58
381
unknown
17
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
74
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 about a year ago
28
235
other
9
R package that makes basic data exploration radically simple (interactive data exploration, reproducible data science)
Created 2018-04-06
594 commits to master branch, last one 24 days 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