Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
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A hyperparameter optimization framework
- python
- machine-learning
- parallel
- distributed
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
AutoML library for deep learning
- automl
- neural-architecture-search
- automated-machine-learning
- python
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
A Hyperparameter Tuning Library for Keras
- automl
- deep-learning
- hyperparameter-optimization
- keras
An Automatic Model Compression (AutoMC) framework for developing smaller and faster AI applications.
- deep-learning
- model-compression
- mobile-app
- automl
✨ Build a machine learning model from a prompt
cubestudio开源云原生一站式机器学习/深度学习/大模型AI平台/MaaS/mlops/人工智能平台/训推平台，算法全链路流程，多租户，算力租赁平台，token中转，拖拉拽任务流pipeline编排，多机多卡分布式训练，超参搜索，推理服务，VGPU虚拟化，云边端协同，边缘计算，自动化标注平台，deepseek等大模型sft微调/奖励模型/强化学习训练，vllm/ollama/mindie大模型多机推理，私有知识库llmops智能体，AI模型市场，支持国产异构算力调度,昇腾/寒武纪/海光/摩尔/沐曦等，支持ib/roce/RDMA，信创支持
Automatic architecture search and hyperparameter optimization for PyTorch
- automl
- deep-learning
- tabular-data
- pytorch
Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization
- hyperopt
- keras
- hyperparameter-optimization
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.
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.