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zenml-io
A repository for all ZenML projects that are specific production use-cases.
A home for machine learning projects built with ZenML and various integrations.
Get everything you need to start a project...
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Roadmap
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Meet the Team
☀️ Introducing ZenML Projects
This repository showcases production-grade ML use cases built with ZenML. The goal of this repository is to provide you a ready-to-use MLOps workflow that you can adapt for your application. We maintain a growing list of projects from various ML domains including time-series, tabular data, computer vision, etc.
🧱 Project List
A list of updated and maintained projects by the ZenML team and the community:
| Project | Tags | Integrations |
|---|---|---|
| NBA Three-Pointer Predictor | Time-series | mlflow kubeflow evidently sklearn aws |
| Time Series Forecasting | Time-series | gcp |
| Customer Satisfaction | Tabular | mlflow kubeflow |
| Customer Churn | Tabular | kubeflow seldon |
| Label Studio Annotation | Data Annotation | label-studio |
| YOLOv5 Object Detection | Computer-vision | mlflow gcp |
| LLMs To Analyze Databases | NLP, LLMs | gcp slack |
| GitFlow ZenML Project | MLOps with ZenML and GitHub Workflows | mlflow deepchecks kserve kubeflow sklearn vertex aws gcp |
| ZenNews | NLP | gcp vertex discord |
| LLM RAG Pipeline with Langchain and OpenAI | NLP, LLMs | slack langchain llama_index |
| Orbit User Analysis | Data Analysis, Tabular | - |
| Huggingface to Sagemaker | NLP | pytorch mlflow huggingface aws s3 kubeflow slack github |
| Complete Guide to LLMs (from RAG to finetuning) | NLP, LLMs | openai supabase |
💻 System Requirements
To run any of the projects listed, you have to install ZenML on your machine. Read our docs for installation details.
- Linux or macOS.
- Python 3.7, 3.8, 3.9 or 3.10
🪃 Contributing
We welcome contributions from anyone to showcase your project built using ZenML. See our contributing guide to start.
🆘 Getting Help
By far the easiest and fastest way to get help is to:
- Ask your questions in our Slack group.
- Open an issue on our GitHub repo.
- Meet the team every week during our community meetup.
🔥 About ZenML
ZenML is an extensible, open-source MLOps framework for creating production-ready ML pipelines. Built for data scientists, it has a simple, flexible syntax, is cloud- and tool-agnostic, and has interfaces/abstractions that are catered towards ML workflows.
If you like these projects and want to learn more:
- Give
the
ZenML Repo
a GitHub Star :star: to show your love! - Join our
Slack Community
and become part of the ZenML family!
📜 License
ZenML Projects is distributed under the terms of the Apache License Version 2.0. A complete version of the license is available in the LICENSE file in this repository. Any contribution made to this project will be licensed under the Apache License Version 2.0.
📖 Learn More
| ZenML Resources | Description |
|---|---|
| 🧘♀️ ZenML 101 | New to ZenML? Here's everything you need to know! |
| ⚛️ Core Concepts | Some key terms and concepts we use. |
| 🚀 Our latest release | New features, bug fixes. |
| 🗳 Vote for Features | Pick what we work on next! |
| 📓 Docs | Full documentation for creating your own ZenML pipelines. |
| 📒 API Reference | Detailed reference on ZenML's API. |
| 👨🍳 MLStacks | Terraform-based infrastructure recipes for pre-made ZenML stacks. |
| ⚽️ Examples | Learn best through examples where ZenML is used. We've got you covered. |
| 📬 Blog | Use cases of ZenML and technical deep dives on how we built it. |
| 🔈 Podcast | Conversations with leaders in ML, released every 2 weeks. |
| 💬 Join Slack | Need help with your specific use case? Say hi on Slack! |
| 🗺 Roadmap | See where ZenML is working to build new features. |
| 🙋♀️ Contribute | How to contribute to the ZenML project and code base. |
zenml-io