ZenML

ZenML is an extensible, open-source MLOps framework for creating portable, production-ready MLOps pipelines. Built to enable collaboration among data scientists, ML Engineers, and MLOps Developers, it has a simple, flexible syntax, is cloud- and tool-agnostic, and has interfaces/abstractions that are thoughtfully designed for ML workflows.

ZenML is not here to replace the great tools that solve these individual problems. Rather, it offers an extensible framework and a standard abstraction to write and build your workflows.

🚀 Website - https://zenml.io
☁️ Sign up - https://cloud.zenml.io
📕 Documentation - https://docs.zenml.io
⭐ GitHub Repository - https://github.com/zenml-io/zenml
🧵 End-To-End Examples - https://github.com/zenml-io/zenml-projects
📞 Join our Slack channel - https://zenml.io/slack

MLOps for Time Series Forecasting with ZenML & Darts
MLOps for Time Series Forecasting with ZenML & Darts
Why ML Engineers Need ZenML: Classical Models + AI Agents, One Framework
Why ML Engineers Need ZenML: Classical Models + AI Agents, One Framework
Evolving MLOps: Foundations for Agentic Workflows
Evolving MLOps: Foundations for Agentic Workflows
ZenML ❤️ llms.txt
ZenML ❤️ llms.txt
ZenML Fundamentals: Your First Step into Production MLOps
ZenML Fundamentals: Your First Step into Production MLOps
VS Code Extension Updates: DAG Visualizer and Stack/Component Registration
VS Code Extension Updates: DAG Visualizer and Stack/Component Registration
Easier MLOps Stacks 3: Infrastructure-as-Code with ZenML Terraform Modules for AWS, GCP, and Azure
Easier MLOps Stacks 3: Infrastructure-as-Code with ZenML Terraform Modules for AWS, GCP, and Azure
Easier MLOps Stacks 2: Easy MLOps Stack Registration Wizard
Easier MLOps Stacks 2: Easy MLOps Stack Registration Wizard
Easier MLOps Stacks I: Introducing 1-click cloud stack deployments
Easier MLOps Stacks I: Introducing 1-click cloud stack deployments
GenAI Model Cards (ZenML Hackathon 2024 Winner)
GenAI Model Cards (ZenML Hackathon 2024 Winner)
Building and Optimizing RAG Pipelines: Data Preprocessing, Embeddings, and Evaluation with ZenML
Building and Optimizing RAG Pipelines: Data Preprocessing, Embeddings, and Evaluation with ZenML
Automating the Workflow: End-to-end MLOps for Computer Vision
Automating the Workflow: End-to-end MLOps for Computer Vision
Run your first MLOps pipeline in 11 minutes | Tutorial
Run your first MLOps pipeline in 11 minutes | Tutorial
ZenML Cloud - Getting Started
ZenML Cloud - Getting Started
[5/5] Huggingface to Sagemaker with ZenML Pipelines - Deploying to AWS Sagemaker Endpoints
[5/5] Huggingface to Sagemaker with ZenML Pipelines - Deploying to AWS Sagemaker Endpoints
[3/5] Huggingface to Sagemaker with ZenML Pipelines - Training a BERT based Sentiment Classifer
[3/5] Huggingface to Sagemaker with ZenML Pipelines - Training a BERT based Sentiment Classifer
[4/5] Huggingface to Sagemaker with ZenML Pipelines - Promoting the model to Production
[4/5] Huggingface to Sagemaker with ZenML Pipelines - Promoting the model to Production
[2/5] Huggingface to Sagemaker with ZenML Pipelines - Feature engineering with a Huggingface Dataset
[2/5] Huggingface to Sagemaker with ZenML Pipelines - Feature engineering with a Huggingface Dataset
[1/5] Huggingface to AWS Sagemaker with ZenML Pipelines - Introduction to the MLOps process
[1/5] Huggingface to AWS Sagemaker with ZenML Pipelines - Introduction to the MLOps process
MLOps Platform Sandbox: Deploy ZenML + Kubeflow + MLflow + Minio in minutes
MLOps Platform Sandbox: Deploy ZenML + Kubeflow + MLflow + Minio in minutes
ZenML Sandbox Demo
ZenML Sandbox Demo
Deploy ZenML on Hugging Face Spaces 🤗
Deploy ZenML on Hugging Face Spaces 🤗
ChatGPT Failure Hooks with ZenML Pipelines
ChatGPT Failure Hooks with ZenML Pipelines
Using Failure and Success Hooks with ZenML
Using Failure and Success Hooks with ZenML
Creating stacks and stack components via the ZenML Dashboard 🌌
Creating stacks and stack components via the ZenML Dashboard 🌌
Outsourcing image builds for your MLOps pipeline to Kaniko, Google Cloud Build, and more!
Outsourcing image builds for your MLOps pipeline to Kaniko, Google Cloud Build, and more!
Log ML Metadata with Neptune - ZenML Integration
Log ML Metadata with Neptune - ZenML Integration
Tool Agnostic MLOps with ZenML - By Hamza Tahir at MLOps Community Munich
Tool Agnostic MLOps with ZenML - By Hamza Tahir at MLOps Community Munich
Deploy and Scale Models with BentoML
Deploy and Scale Models with BentoML
Team Fuzzy Labs - 1st Place in ZenML Month of MLOps 2022
Team Fuzzy Labs - 1st Place in ZenML Month of MLOps 2022