Scikit Learn
Showing 36 of 115 projects
HyperLearn provides 2-2000x faster machine learning algorithms with 50% less memory usage, optimized for all hardware.
An intuitive Python library that adds single-line plotting functions for scikit-learn and other machine learning objects.
A modular active learning framework for Python built on scikit-learn, enabling rapid creation of custom workflows.
A modular active learning framework for Python built on scikit-learn, enabling rapid creation of custom workflows.
A Python library for feature engineering and selection with scikit-learn compatible transformers.
Automatically visualize any dataset with a single line of code, including data quality assessment and fixes.
A Python library for probabilistic prediction using natural gradient boosting, built on scikit-learn.
Genetic Programming in Python, with a scikit-learn inspired API
Automated machine learning library for production and analytics, handling feature engineering, model selection, and hyperparameter optimization.
Hyperopt-sklearn automates hyperparameter optimization and model selection for scikit-learn machine learning pipelines.
Python implementation of the Boruta all-relevant feature selection method with scikit-learn compatibility.
A Python package for concise, transparent, and accurate predictive modeling with sklearn-compatible interpretable models.
An open-source Python repository providing around 40 feature selection algorithms for machine learning applications.
MLeap is a portable execution engine for deploying machine learning pipelines from Spark and Scikit-learn without their runtime dependencies.
A Python library for time series forecasting using scikit-learn compatible machine learning models.
A Python library for time series forecasting using scikit-learn compatible machine learning models.
Metric learning algorithms in Python
Metric learning algorithms in Python
A free software AI accelerator that speeds up scikit-learn applications by 10-100x on CPUs and GPUs with no code changes.
Implementation of hyperparameter optimization methods for ML/DL models with sample code for regression and classification tasks.
Survival analysis built on top of scikit-learn
Transpile trained scikit-learn estimators to C, Java, JavaScript, Go, PHP, and Ruby for embedded systems and performance-critical applications.
A web-based tool for automated hyperparameter tuning and stacked ensemble creation in Python.
PySpark + Scikit-learn = Sparkit-learn
A Python library implementing Factorization Machines with a scikit-learn compatible API for regression, classification, and ranking tasks.
A scikit-learn compatible Python module for multi-label classification tasks.
Combines the ease of use of scikit-learn with the power of Theano/Lasagne
A Python library for building high-performance, memory-efficient ensemble learning networks with a Scikit-learn compatible API.
A Python machine learning package for incremental learning on streaming data with concept drift detection.
A collection of IPython notebooks demonstrating data analysis and machine learning techniques on security datasets.
A scikit-learn compatible hyperparameter optimization tool using evolutionary algorithms instead of grid search.
A fast GPU-accelerated library for training Gradient Boosting Decision Trees (GBDT) and Random Forests.
IPython-based environment for reproducible machine learning research with unified wrappers for multiple ML libraries.
A Python package for stacking (stacked generalization) with both functional and scikit-learn compatible APIs.
A fast, robust Python library to detect offensive language in text using a machine learning model.
A high-performance C++/DPC++ library for accelerated machine learning on CPUs, GPUs, and distributed systems.
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