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 | ||||||||||
Alink | 3,479 | 16 | a month ago | 19 | November 03, 2023 | 53 | apache-2.0 | Java | ||
Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform. | ||||||||||
Pycm | 1,413 | 5 | 13 | 3 months ago | 44 | June 07, 2023 | 12 | mit | Python | |
Multi-class confusion matrix library in Python | ||||||||||
Awesome Fraud Detection Papers | 1,364 | a year ago | cc0-1.0 | Python | ||||||
A curated list of data mining papers about fraud detection. | ||||||||||
Graph Adversarial Learning Literature | 772 | 4 months ago | ||||||||
A curated list of adversarial attacks and defenses papers on graph-structured data. | ||||||||||
R | 745 | 5 months ago | 11 | mit | R | |||||
Collection of various algorithms implemented in R. | ||||||||||
Awesome Ai For Time Series Papers | 627 | 7 months ago | mit | |||||||
A professional list of Papers, Tutorials, and Surveys on AI for Time Series in top AI conferences and journals. | ||||||||||
Pypots | 558 | 3 months ago | 20 | November 30, 2023 | 14 | bsd-3-clause | Python | |||
A Python toolbox/library for reality-centric machine learning/deep learning on partially-observed time series with PyTorch, including SOTA models supporting tasks of imputation, classification, clustering, and forecasting on incomplete (irregularly-sampled) multivariate time series with NaN missing values/data. https://arxiv.org/abs/2305.18811 | ||||||||||
Rmdl | 409 | 1 | a year ago | 7 | July 01, 2020 | 2 | gpl-3.0 | Python | ||
RMDL: Random Multimodel Deep Learning for Classification | ||||||||||
Automlpipeline.jl | 331 | 8 months ago | 21 | mit | HTML | |||||
A package that makes it trivial to create and evaluate machine learning pipeline architectures. |