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Top 23 Jupyter Notebook Mlops Projects
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AppSignal
AppSignal knows why the f*#k it crashed. Stop vibe-debugging. Every exception, every backtrace, grouped so you see patterns, not noise.
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agents-towards-production
End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.
Project mention: Show HN: GibRAM an in-memory ephemeral GraphRAG runtime for retrieval | news.ycombinator.com | 2026-01-17GraphRAG's approach certainly makes sense for regulation-heavy documents, where interconnected references can be critical for retrieval quality. The challenge you mentioned about separate systems for graph storage and vector indexing resonates with what we've seen in the field. In practice, this separation often adds unnecessary complexity for ephemeral analysis tasks. One thing we've explored is using a dual-memory architecture, which might be relevant here even in an in-memory context. It allows you to effectively manage recent context and longer-term semantic connections without the overhead of persistent storage. If you're interested in seeing how this approach could be integrated into production systems, I wrote up some patterns that might be useful: https://github.com/NirDiamant/agents-towards-production.
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mlops-zoomcamp
Free MLOps course from DataTalks.Club. Register here 👇🏼 to get notified about the next cohort
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amazon-sagemaker-examples
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
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evidently
Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.
Project mention: Why Your Neural Network Fails Silently and How to Actually Debug It | dev.to | 2026-04-25Set up drift detection. Compare weekly distributions of model inputs against your training data baseline. Tools like Evidently make this straightforward.
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higgsfield
Fault-tolerant, highly scalable GPU orchestration, and a machine learning framework designed for training models with billions to trillions of parameters
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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whylogs
An open-source data logging library for machine learning models and data pipelines. 📚 Provides visibility into data quality & model performance over time. 🛡️ Supports privacy-preserving data collection, ensuring safety & robustness. 📈
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hamilton
Apache Hamilton helps data scientists and engineers define testable, modular, self-documenting dataflows, that encode lineage/tracing and metadata. Runs and scales everywhere python does.
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mlops-python-package
Production-shaped MLOps Python package and reference implementation of the MLOps Coding Course: MLflow, scikit-learn, Pydantic, Pandera, uv, and mise.
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vertex-ai-samples
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.
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serverless-ml-course
Serverless Machine Learning Course for building AI-enabled Prediction Services from models and features
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MLSys-NYU-2022
Slides, scripts and materials for the Machine Learning in Finance Course at NYU Tandon, 2022
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fsdl-text-recognizer-2022-labs
Complete deep learning project developed in Full Stack Deep Learning, 2022 edition. Generated automatically from https://github.com/full-stack-deep-learning/fsdl-text-recognizer-2022
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mlops-projects
Hands-on MLOps projects to explore and learn the practical aspects of machine learning engineering for production.
Project mention: 7 MLOps Projects (Beginner-Friendly) That Teach Real Production Skills | dev.to | 2026-02-24An experiment tracking tool (e.g., MLflow Tracking) to log runs and metrics; you can also reference this GitHub repo of mlops-projects for additional examples
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TorchServe: Model Serving for PyTorch
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examples
📝 Examples of how to use Neptune for different use cases and with various MLOps tools (by neptune-ai)
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
Jupyter Notebook Mlops discussion
Jupyter Notebook Mlops related posts
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Arize Phoenix: observability tool for experimentation and evaluation of LLMs
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Should I Use a Framework to Build an Agent? Code vs. LangGraph vs. Workflows
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Wk 4: Deployment - MLOPs with DataTalks
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Wk 2 Experiment Tracking: MLOPs with DataTalks
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Wk 1: MLOPs with DataTalks
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Created a plastic object detection model using AWS technologies 🌍🤖
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Created a plastic object detection model using AWS technologies 🌍🤖
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A note from our sponsor - SaaSHub
www.saashub.com | 9 Oct 2026
Index
What are some of the best open-source Mlops projects in Jupyter Notebook? This list will help you:
| # | Project | Stars |
|---|---|---|
| 1 | Made-With-ML | 49,672 |
| 2 | agents-towards-production | 21,532 |
| 3 | mlops-zoomcamp | 15,376 |
| 4 | amazon-sagemaker-examples | 10,990 |
| 5 | evidently | 7,968 |
| 6 | higgsfield | 4,097 |
| 7 | mlops-course | 3,392 |
| 8 | whylogs | 2,834 |
| 9 | hamilton | 2,605 |
| 10 | MLOps | 2,111 |
| 11 | mlops-python-package | 1,419 |
| 12 | efficient-dl-systems | 1,040 |
| 13 | vertex-ai-samples | 792 |
| 14 | serverless-ml-course | 684 |
| 15 | MLSys-NYU-2022 | 559 |
| 16 | fsdl-text-recognizer-2022-labs | 529 |
| 17 | fake-news | 171 |
| 18 | mlops-projects | 112 |
| 19 | serving-pytorch-models | 102 |
| 20 | examples | 87 |
| 21 | whylogs-examples | 49 |
| 22 | mltraq | 43 |
| 23 | ml-pipeline-engineering | 35 |
Sponsored
AppSignal knows why the f*#k it crashed.
Stop vibe-debugging. Every exception, every backtrace, grouped so you see patterns, not noise.
www.appsignal.com