https://github.com/zenml-io/zenml-projects

A repository for all ZenML projects that are specific production use-cases.
https://github.com/zenml-io/zenml-projects

Last synced: 25 days ago
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A repository for all ZenML projects that are specific production use-cases.

Host: GitHub
URL: https://github.com/zenml-io/zenml-projects
Owner: zenml-io
License: apache-2.0
Created: 2022-02-01T10:14:52.000Z (over 3 years ago)
Default Branch: main
Last Pushed: 2025-05-07T16:39:39.000Z (about 1 month ago)
Last Synced: 2025-05-11T14:15:32.438Z (30 days ago)
Language: Jupyter Notebook
Size: 665 MB
Stars: 255
Watchers: 7
Forks: 60
Open Issues: 5
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE-OF-CONDUCT.md

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README

        







  

    

  

A home for machine learning projects built

with ZenML and various

integrations.


  


    Get everything you need to start a project...

    

    


    Features

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    Roadmap

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    Report Bug

    ·

    Vote New Features

    ·

    Read Blog

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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                                                   | Domain    | Key Features                               | Core Technologies                    |

| --------------------------------------------------------- | --------- | ------------------------------------------ | ------------------------------------ |

| [ZenML Support Agent](zenml-support-agent)                | 🤖 LLMOps | 🔍 RAG, 📊 Vector DB, 💬 Conversational    | langchain, llama_index, openai       |

| [ZenCoder](zencoder)                                      | 🤖 LLMOps | 🧠 Fine-tuning, 📈 Transfer Learning       | huggingface, pytorch, wandb          |

| [Complete Guide to LLMs](llm-complete-guide)              | 🤖 LLMOps | 🔍 RAG, 🧠 Fine-tuning, 📊 Evaluation      | openai, huggingface, anthropic       |

| [Gamesense](gamesense)                                    | 🤖 LLMOps | 🧠 LoRA, ⚡ Efficient Training             | pytorch, peft, phi-2                 |

| [Nightwatch AI](nightwatch-ai)                            | 🤖 LLMOps | 📝 Summarization, 📊 Reporting             | openai, supabase, slack              |

| [ResearchRadar](research-radar)                           | 🤖 LLMOps | 📝 Classification, 📊 Comparison           | anthropic, huggingface, transformers |

| [End-to-end Computer Vision](end-to-end-computer-vision)  | 👁️ Vision | 🎯 Object Detection, 🏷️ Labeling           | pytorch, label_studio, yolov8        |

| [Magic Photobooth](magic-photobooth)                      | 👁️ Vision | 🖼️ Image Gen, 🎬 Video Gen                 | stable-diffusion, huggingface        |

| [OmniReader](omni-reader)                                 | 👁️ Vision | 📝 OCR, 📊 Evaluation, 🔄 Batch Processing | polars, litellm, openai, ollama      |

| [Oncoclear](oncoclear)                                    | 🚀 MLOps  | 📦 Deployment, 🔄 CI/CD                    | docker, kubernetes, scikit-learn     |

| [Sign Language Detection](sign-language-detection-yolov5) | 👁️ Vision | 🎯 Object Detection, ⚡ Real-time          | mlflow, bentoml, vertex-ai           |

| [Huggingface to Sagemaker](huggingface-sagemaker)         | 🚀 MLOps  | 🔄 CI/CD, 📦 Deployment                    | mlflow, sagemaker, kubeflow          |

| [Databricks Production QA](databricks-production-qa-demo) | 🚀 MLOps  | 📊 Monitoring, 🔍 Quality Assurance        | databricks, evidently, shap          |

| [Eurorate Predictor](eurorate-predictor)                  | 📊 Data   | ⏱️ Time Series, 🔄 ETL                     | airflow, bigquery, xgboost           |

| [RetailForecast](retail-forecast)                         | 📊 Data   | ⏱️ Time Series, 📈 Forecasting, 🔮 Multi-Model | prophet, zenml, pandas                |

# 💻 System Requirements

To run any of the projects listed, you have to install ZenML on your machine.

Read [our docs](https://docs.zenml.io/getting-started/installation) for

installation details.

- Linux or macOS.

- Python >=3.9

# 🪃 Contributing

We welcome contributions from anyone to showcase your project built using ZenML.

See our [contributing guide](./CONTRIBUTING.md) to start.

# 🆘 Getting Help

By far the easiest and fastest way to get help is to:

* Ask your questions in [our Slack group](https://zenml.io/slack/).

* [Open an issue](https://github.com/zenml-io/zenml-dashboard/issues/new/choose)

  on our GitHub repo.

# 🔥 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](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.                                      |

| ⚽️ **[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 101]: https://docs.zenml.io/user-guides/starter-guide

[Core Concepts]: https://docs.zenml.io/getting-started/core-concepts

[Our latest release]: https://github.com/zenml-io/zenml/releases

[Vote for Features]: https://zenml.io/discussion

[Docs]: https://docs.zenml.io/

[API Reference]: https://apidocs.zenml.io/

[Examples]: https://github.com/zenml-io/zenml/tree/main/examples

[Blog]: https://blog.zenml.io/

[Podcast]: https://podcast.zenml.io/

[Join Slack]: https://zenml.io/slack-invite/

[Roadmap]: https://zenml.io/roadmap

[Contribute]: https://github.com/zenml-io/zenml/blob/main/CONTRIBUTING.md