Ml4bio
A graphical interface for sklearn classification to introduce machine learning to biologists
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Mapie | 1,089 |  | 5 | 3 months ago | 21 | September 14, 2023 | 40 | bsd-3-clause | Jupyter Notebook | |
| A scikit-learn-compatible module for estimating prediction intervals. | ||||||||||
| Sklearn Classification | 402 | 6 years ago | 4 | gpl-3.0 | Jupyter Notebook | |||||
| Data Science Notebook on a Classification Task, using sklearn and Tensorflow. | ||||||||||
| Machine Learning | 397 | 2 years ago | mit | Python | ||||||
| Implementation of different ML Algorithms from scratch, written in Python 3.x | ||||||||||
| Gam | 257 | a year ago | 1 | gpl-3.0 | Python | |||||
| A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018). | ||||||||||
| Imbalanced Ensemble | 234 |  | 4 | 9 months ago | 10 | July 22, 2023 | mit | Python | ||
| Class-imbalanced Ensemble Learning in Python. | 类别不平衡/长尾机器学习库 | ||||||||||
| Mnist_tutorial | 222 | 3 years ago | 2 | Jupyter Notebook | ||||||
| A tutorial for MNIST handwritten digit classification using sklearn, PyTorch and Keras. | ||||||||||
| Machine Learning Projects | 163 | 3 years ago | 2 | Jupyter Notebook | ||||||
| This repository consists of all my Machine Learning Projects. | ||||||||||
| Snape | 151 | 4 years ago | 2 | apache-2.0 | Python | |||||
| Snape is a convenient artificial dataset generator that wraps sklearn's make_classification and make_regression and then adds in 'realism' features such as complex formating, varying scales, categorical variables, and missing values. | ||||||||||
| Tiny_ml | 137 | 4 years ago | Python | |||||||
| numpy 实现的 周志华《机器学习》书中的算法及其他一些传统机器学习算法 | ||||||||||
| Sklearn Hierarchical Classification | 131 |  | 1 | 1 | 4 years ago | 5 | January 09, 2020 | 13 | apache-2.0 | Python |
| Hierarchical classification module based on scikit-learn's interfaces | ||||||||||
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