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
Distributed Asynchronous Hyperparameter Optimization in Python
- hacktoberfest
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
A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
- rl
- reinforcement-learning
- stable-baselines
- openai
✨ 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
[ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deployment
- tinyml
- edge-ai
- efficient-model
- acceleration
Ergonomic machine learning for everyone.
- machine-learning
- neural-networks
- auto-ml
Provide an input CSV and a target field to predict, generate a model + code to run it.
- python
- tensorflow
- keras
- xgboost
Hyper-parameter optimization for sklearn