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.
Parallel computing with task scheduling
Fast and Accurate ML in 3 Lines of Code
Open Machine Learning Course
Open-source, low-code AutoML platform for Python. PyCaret 4.0: sklearn-native engine + React control plane.
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.
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
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 library for time series forecasting using scikit-learn compatible models, statistical methods, and foundation models
Metric learning algorithms in Python
PySpark + Scikit-learn = Sparkit-learn
Hyperparameter optimization and feature selection for scikit-learn using evolutionary algorithms. A modern alternative to GridSearchCV and RandomizedSearchCV.
Python package implementing ML feature engineering and pre-processing for polars or pandas dataframes.