1.onnx / onnx
Open standard for machine learning interoperability
Ranked by Attention Score: stars gained over the last 180 complete days
29 repositories by Attention Score · May 7, 2026 – Nov 2, 2026 (UTC)
Open standard for machine learning interoperability
AiLearning:数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2
Python library for portfolio optimization, factor model construction, and risk management built on scikit-learn
Fast and Accurate ML in 3 Lines of Code
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
A unified framework for machine learning with time series
Open Machine Learning Course
Parallel computing with task scheduling
Open-source, low-code AutoML platform for Python. PyCaret 4.0: sklearn-native engine + React control plane.
Automated Machine Learning with scikit-learn
An open source python library for automated feature engineering
Feature engineering and selection open-source Python library compatible with sklearn.
Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models
Genetic Programming in Python, with a scikit-learn inspired API
Seamlessly integrate LLMs into scikit-learn.
Hyperparameter optimization and feature selection for scikit-learn using evolutionary algorithms. A modern alternative to GridSearchCV and RandomizedSearchCV.
Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies
A modular active learning framework for Python
Extra blocks for scikit-learn pipelines.
Visual analysis and diagnostic tools to facilitate machine learning model selection.
Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
Sequential model-based optimization with a `scipy.optimize` interface
Python package implementing ML feature engineering and pre-processing for polars or pandas dataframes.
An intuitive library to add plotting functionality to scikit-learn objects.
Metric learning algorithms in Python
Transpile trained scikit-learn estimators and transformers to C, C#, Go, Java, JavaScript, PHP and Ruby.
PySpark + Scikit-learn = Sparkit-learn
A scikit-learn based module for multi-label et. al. classification
Stacked Generalization (Ensemble Learning)