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
85,081 visible repositories in the index
1–22 of 22 · Most stars
Fast and Accurate ML in 3 Lines of Code
Open-source, low-code AutoML platform for Python. PyCaret 4.0: sklearn-native engine + React control plane.
- data-science
- python
- machine-learning
- pycaret
Automated Machine Learning with scikit-learn
- automl
- scikit-learn
- automated-machine-learning
- hyperparameter-optimization
Scalable and user friendly neural :brain: forecasting algorithms.
- deep-learning
- forecasting
- esrnn
- nbeats
Symbolic Learning in Python and Julia
- symbolic-regression
- machine-learning
- python
- julia
Differentiable architecture search for convolutional and recurrent networks
- deep-learning
- automl
- image-classification
- language-modeling
Python AutoML toolkit for benchmarking classification, regression, and time-series forecasting models, with GPU acceleration, MLflow tracking, and automated preprocessing.
- machine-learning
- automl
- regression
- classification
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
a delightful machine learning tool that allows you to train, test, and use models without writing code
- machine-learning
- machinelearning
- machine-learning-algorithms
- machine-learning-library
An Automatic Model Compression (AutoMC) framework for developing smaller and faster AI applications.
- deep-learning
- model-compression
- mobile-app
- automl
Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization
- hyperopt
- keras
- hyperparameter-optimization
Python AutoML for Trading Systems and Sports Betting
- machine-learning
- predictive-analytics
- classification
- regression
OpenMMLab Model Compression Toolbox and Benchmark.
- nas
- pruning
- knowledge-distillation
- spos
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
- vizier
- hyperparameter-optimization
- tuning
- tuning-parameters
TODS: An Automated Time-series Outlier Detection System
- outlier-detection
- automl
- anomaly-detection
- machine-learning
Official Implementation of 'Fast AutoAugment' in PyTorch.
- deep-learning
- convolutional-neural-networks
- pytorch
- augmentation
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
The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.
- pipeline
- pipeline-framework
- machine-learning
- deep-learning
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.