Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Repository Index
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1–19 of 19 · Most stars
Fast and Accurate ML in 3 Lines of Code
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
- machine-learning
- python
- data-science
- automl
Open-source, low-code AutoML platform for Python. PyCaret 4.0: sklearn-native engine + React control plane.
- data-science
- python
- machine-learning
- pycaret
AutoML library for deep learning
- automl
- neural-architecture-search
- automated-machine-learning
- python
H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
Scalable and user friendly neural :brain: forecasting algorithms.
- deep-learning
- forecasting
- esrnn
- nbeats
AI Infra / AI Orchestration / AI Control Plane
Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.
- deep-learning
- machine-learning
- ml-platform
- ml-infrastructure
Automatic architecture search and hyperparameter optimization for PyTorch
- automl
- deep-learning
- tabular-data
- pytorch
Machine Learning in R
- machine-learning
- data-science
- tuning
- cran
MLBox is a powerful Automated Machine Learning python library.
- machine-learning
- auto-ml
- kaggle
- deep-learning
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
- bayesian-optimization
- bayesian-optimisation
- hyperparameter-optimization
- hyperparameter-tuning
An autoML framework & toolkit for machine learning on graphs.
Machine Learning toolbox for Humans
Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.
- python
- pytorch
- machine-learning
- deep-learning
Hyperparameter optimization and feature selection for scikit-learn using evolutionary algorithms. A modern alternative to GridSearchCV and RandomizedSearchCV.
A hyperparameter optimization framework, inspired by Optuna.
- bayesian-optimization
- bandit-algorithms
- evolution-strategies
- blackbox-optimization
Support vector machines (SVMs) and related kernel-based learning algorithms are a well-known class of machine learning algorithms, for non-parametric classification and regression. liquidSVM is an implementation of SVMs whose key features are: fully integrated hyper-parameter selection, extreme speed on both small and large data sets, full flexibility for experts, and inclusion of a variety of different learning scenarios: multi-class classification, ROC, and Neyman-Pearson learning, and least-squares, quantile, and expectile regression.
- svm
- regression
- classification
- machine-learning