A home for machine learning projects built with ZenML and various integrations.
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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 | 🤖 LLMOps | 🔍 RAG, 📊 Vector DB, 💬 Conversational | langchain, llama_index, openai |
| ZenCoder | 🤖 LLMOps | 🧠 Fine-tuning, 📈 Transfer Learning | huggingface, pytorch, wandb |
| Complete Guide to LLMs | 🤖 LLMOps | 🔍 RAG, 🧠 Fine-tuning, 📊 Evaluation | openai, huggingface, anthropic |
| Gamesense | 🤖 LLMOps | 🧠 LoRA, ⚡ Efficient Training | pytorch, peft, phi-2 |
| Nightwatch AI | 🤖 LLMOps | 📝 Summarization, 📊 Reporting | openai, supabase, slack |
| ResearchRadar | 🤖 LLMOps | 📝 Classification, 📊 Comparison | anthropic, huggingface, transformers |
| End-to-end Computer Vision | 👁 CV | 🔎 Object Detection, 🏷️ Labeling | pytorch, label_studio, yolov8 |
| Magic Photobooth | 👁 CV | 📷 Image Gen, 🎞️ Video Gen | stable-diffusion, huggingface |
| OmniReader | 👁 CV | 📑 OCR, 📊 Evaluation, ⚙️ Batch Processing | polars, litellm, openai, ollama |
| Sign Language Detection | 👁 CV | 🔎 Object Detection, ⚡ Real-time | mlflow, bentoml, vertex-ai |
| Oncoclear | 🚀 MLOps | 📦 Deployment, 🔄 CI/CD | docker, kubernetes, scikit-learn |
| Huggingface to Sagemaker | 🚀 MLOps | 🔄 CI/CD, 📦 Deployment | mlflow, sagemaker, kubeflow |
| Databricks Production QA | 🚀 MLOps | 📊 Monitoring, 🔍 Quality Assurance | databricks, evidently, shap |
| Vertex Registry and Deployer | 🚀 MLOps | 📦 Model Registry, 🚀 Deployment | vertex, gcp, zenml |
| Eurorate Predictor | 📊 Data | ⏱️ Time Series, 🧹 ETL | airflow, bigquery, xgboost |
| RetailForecast | 📊 Data | ⏱️ Time Series, 📈 Forecasting, 🔄 Multi-Model | prophet, zenml, pandas |
| Bank Subscription Prediction | 📊 Data | 💼 Classification, ⚖️ Imbalanced Data, 🔍 Feature Selection | xgboost, plotly, zenml |
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 >=3.9
We welcome contributions from anyone to showcase your project built using ZenML. See our contributing guide to start.
All code contributions must pass our automated code quality checks:
- Code Formatting: We use ruff for code formatting and linting
- Spelling: We check for typos and spelling errors
- Markdown Links: We verify that all links in documentation work properly
Our CI pipeline will automatically check your PR for these issues. Remember to run bash scripts/format.sh locally before submitting your PR to ensure it passes the formatting checks.
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.
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:
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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.
| ZenML Resources | Description |
|---|---|
| 🧘 [ZenML 101] | New to ZenML? Here's everything you need to know! |
| ⚛ [Core Concepts] | Understand ZenML's building blocks. |
| 🚀 [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] | Explore more sample projects. |
| 📬 [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] | Got a PR or feature request? Start here. |
| [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 |