Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
-
Updated
Jul 16, 2024 - Python
Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.
SensiML's open-source AutoML solution for Edge AI model development
Analytics & Machine Learning R Sidekick
Automated Machine Learning on Kubernetes
A package that makes it trivial to create and evaluate machine learning pipeline architectures.
Train, Evaluate, Optimize, Deploy Computer Vision Models via OpenVINO™
Notebooks, code samples, sample apps, and other resources that demonstrate how to use, develop and manage machine learning and generative AI workflows using Google Cloud Vertex AI.
A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
Join us
Fast and Accurate ML in 3 Lines of Code
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.
High-Performance Symbolic Regression in Python and Julia
Distributed High-Performance Symbolic Regression in Julia
Lightning ⚡️ fast forecasting with statistical and econometric models.
Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools.
An open source python library for automated feature engineering
My portfolio series of ML projects in Jupyter notebooks focused on training algorithms and tuning them.
Easy Volumetric Segmentation with Deep Learning
Add a description, image, and links to the automl topic page so that developers can more easily learn about it.
To associate your repository with the automl topic, visit your repo's landing page and select "manage topics."