scikit-learn: machine learning in Python
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AiLearning：数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2
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.
Open standard for machine learning interoperability
Parallel computing with task scheduling
Fast and Accurate ML in 3 Lines of Code
Open Machine Learning Course
A unified framework for machine learning with time series
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
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning
Visual analysis and diagnostic tools to facilitate machine learning model selection.
Seamlessly integrate LLMs into scikit-learn.
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
Pandas integration with sklearn
Python library for portfolio optimization, factor model construction, and risk management built on scikit-learn
An intuitive library to add plotting functionality to scikit-learn objects.
A modular active learning framework for Python
Feature engineering and selection open-source Python library compatible with sklearn.
Automatically Visualize any dataset, any size with a single line of code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.
Genetic Programming in Python, with a scikit-learn inspired API
Python implementations of the Boruta all-relevant feature selection method.
Python library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models