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- Technical Debt in Machine Learning Systems (2015) [pdf] http://papers.nips.cc/paper/5656-hidden-technical-debt-in-machine-learning-systems.pdf 5 comments
- Hidden Technical Debt in Machine Learning Systems (2015) [pdf] http://papers.nips.cc/paper/5656-hidden-technical-debt-in-machine-learning-systems.pdf 2 comments
Linking pages
- Why We Need DevOps for ML Data | Tecton https://tecton.ai/blog/devops-ml-data/ 87 comments
- notes/Machine Learning.md at master · brylevkirill/notes · GitHub https://github.com/brylevkirill/notes/blob/master/Machine%20Learning.md 8 comments
- Getting Better at Machine Learning | by Robert Chang | Medium https://medium.com/@rchang/getting-better-at-machine-learning-16b4dd913a1f 5 comments
- How to become a Machine Learning Engineer in 2020 | by Jeffrey Luppes | Towards Data Science https://towardsdatascience.com/how-to-become-a-machine-learning-engineer-in-2020-1161aa29261e 5 comments
- Nitpicking Machine Learning Technical Debt - matthewmcateer.me https://matthewmcateer.me/blog/machine-learning-technical-debt/ 3 comments
- First Impressions of Data Science Version Control (DVC) | by Christopher Samiullah | Medium https://medium.com/@christopher.samiullah/first-impressions-of-data-science-version-control-dvc-fe96ab29cdda#fd57 3 comments
- GitHub - eugeneyan/applied-ml: 📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production. https://github.com/eugeneyan/applied-ml 2 comments
- Technical debt: probably the main roadblack in applying machine learning to medicine | Andrew T McKenzie http://andrewtmckenzie.com/2015/12/14/technical-debt-probably-the-main-roadblack-in-applying-machine-learning-to-medicine/ 2 comments
- The 7 Questions You Need to Ask to Operate Deep Learning Infrastructure at Scale — James Le https://jameskle.com/writes/deep-learning-infrastructure-tooling 1 comment
- Hello World — Raven Protocol. First truly distributed and… | by Raven Protocol | RavenProtocol | Medium https://medium.com/ravenprotocol/hello-world-raven-protocol-f749bf5fc8cf 1 comment
- MLOps — Why You’d Want It In Your Company Today | by Roy Peleg | Nanit Engineering https://engineering.nanit.com/mlops-why-youd-want-it-in-your-company-today-2244af505d5a?gi=dbc5ea3ed1fa 1 comment
- Artificial Intelligence: a concise conceptual introduction | Towards Data Science https://medium.com/@leandromineti/artificial-intelligence-d1e45efc99b4 1 comment
- Three Risks in Building Machine Learning Systems https://insights.sei.cmu.edu/sei_blog/2020/05/three-risks-in-building-machine-learning-systems 0 comments
- AI Engineering: 11 Foundational Practices for Decision Makers https://insights.sei.cmu.edu/sei_blog/2019/12/ai-engineering-11-foundational-practices-for-decision-makers.html 0 comments
- Technical Debt in Machine Learning | by Maksym Zavershynskyi | Towards Data Science https://towardsdatascience.com/technical-debt-in-machine-learning-8b0fae938657 0 comments
- The 5 Components Towards Building Production-Ready Machine Learning Systems — James Le https://jameskle.com/writes/testing-and-deployment 0 comments
- What are Symbolic and Imperative APIs in TensorFlow 2.0? | by TensorFlow | TensorFlow | Medium https://medium.com/tensorflow/what-are-symbolic-and-imperative-apis-in-tensorflow-2-0-dfccecb01021 0 comments
- Mythbusters Reloaded: 7 More Myths About AI | by Sebastian Schaal | Luminovo | Medium https://medium.com/p/7b761e64b24b 0 comments
- First Impressions of Data Science Version Control (DVC) https://christophergs.github.io/machine%20learning/2019/05/13/first-impressions-of-dvc/ 0 comments
- Outperforming Google Cloud AutoML Vision with Tensorflow | by Shane Keller | Towards Data Science https://towardsdatascience.com/outperforming-google-cloud-automl-vision-with-tensorflow-and-google-deep-learning-vm-34a45e3860ae 0 comments
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