Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Orange3 | 4,469 | 57 | 47 | 3 months ago | 63 | October 31, 2023 | 99 | other | Python | |
🍊 :bar_chart: :bulb: Orange: Interactive data analysis | ||||||||||
Machine Learning With Python | 2,980 | a year ago | 8 | bsd-2-clause | Jupyter Notebook | |||||
Practice and tutorial-style notebooks covering wide variety of machine learning techniques | ||||||||||
Mljar Supervised | 2,867 | 2 | 3 months 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 | ||||||||||
Dtreeviz | 2,720 | 2 | 22 | 3 months ago | 41 | July 07, 2022 | 61 | mit | Jupyter Notebook | |
A python library for decision tree visualization and model interpretation. | ||||||||||
Awesome Decision Tree Papers | 2,266 | 3 months ago | 1 | cc0-1.0 | Python | |||||
A collection of research papers on decision, classification and regression trees with implementations. | ||||||||||
Text_classification | 1,621 | a year ago | 1 | mit | Python | |||||
Text Classification Algorithms: A Survey | ||||||||||
Awesome Gradient Boosting Papers | 930 | 10 months ago | 1 | cc0-1.0 | Python | |||||
A curated list of gradient boosting research papers with implementations. | ||||||||||
Ai_all_resources | 647 | 5 months ago | 1 | Jupyter Notebook | ||||||
A curated list of Best Artificial Intelligence Resources | ||||||||||
Decision Forests | 635 | 5 | 3 months ago | 33 | November 20, 2023 | 35 | apache-2.0 | Python | ||
A collection of state-of-the-art algorithms for the training, serving and interpretation of Decision Forest models in Keras. | ||||||||||
Chefboost | 428 | 4 months ago | 17 | February 16, 2022 | mit | Python | ||||
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 features support for Python |