bodywork-pipeline-with-aporia-monitoring
Made-With-ML
bodywork-pipeline-with-aporia-monitoring | Made-With-ML | |
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1 | 51 | |
4 | 35,702 | |
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0.0 | 6.8 | |
almost 2 years ago | 5 months ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT License | MIT License |
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bodywork-pipeline-with-aporia-monitoring
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Calling Aporia from Bodywork Pipelines to Monitor Models in Production
Monitoring models for drift and degradation is not easy - theoretically or practically. In this example project we show to outsource these problems to Aporia’s model monitoring platform, by using their Python client from within a Bodywork pipeline.
Made-With-ML
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[D] How do you keep up to date on Machine Learning?
Made With ML
- Open-Source Production Machine Learning Course
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Advice for switching careers within analytics
- Develop a (simple!) ML project and apply MLOps best practices to it. Ask Chat GPT all of your MLOps questions. I've joined this MLOps community and it has been very helpful to know what path to follow in order to be better at MLOps, thanks to them I arrived at madewithml, but I haven't done it yet. But it covers all the MLOps side.
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Recommendation for MLOps resources
Hey, I’m also working in ML. Here’s a great resource: https://madewithml.com. Also, check out Noah Gift’s book Practical MLOPs.
- Ask HN: Resource to learn how to train and use ML Models
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Need help to find resources to learn ml ops
Try replicating this setup: https://madewithml.com/
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MLops Resources
madewithml
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Ask HN: How do I get started with MLOps?
There's a really nice website by Goku Mohandas called Made With ML. IMO it is the best practical guide to MLOps out there: https://madewithml.com
Incase you want to dive a little deeper, https://fullstackdeeplearning.com/course/2022/ is also something I have been recommended by folks.
- Resources for Current DE Interested in Learning Data Science
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Do organizations still need machine learning engineers?
madewithml is pretty sweet, especially the MLOps side of things. It'll give you good skills in how development in Python and deploying ML works.
What are some alternatives?
evidently - Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b
zero-to-mastery-ml - All course materials for the Zero to Mastery Machine Learning and Data Science course.
VevestaX - 2 Lines of code to track ML experiments + EDA + check into Github
mlops-zoomcamp - Free MLOps course from DataTalks.Club
bodywork-pymc3-project - Serving Uncertainty with Bayesian inference, using PyMC3 with Bodywork
FLAML - A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
ML-Workspace - 🛠 All-in-one web-based IDE specialized for machine learning and data science.
mlops-course - Learn how to design, develop, deploy and iterate on production-grade ML applications.
ml-pipeline-engineering - Best practices for engineering ML pipelines.
practical-mlops-book - [Book-2021] Practical MLOps O'Reilly Book
bodywork - ML pipeline orchestration and model deployments on Kubernetes.
Copulas - A library to model multivariate data using copulas.