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- Nicola Bortignon - My favorite papers of 2017 http://www.nicolabortignon.com/my-favorite-4-papers-of-2017/ 16 comments
- The Data Science Workflow. Suppose you are starting a new data… | by Konstantin | Towards Data Science https://medium.com/@kt.era.ee/the-data-science-workflow-43859db0415 9 comments
- Polyaxon, Argo and Seldon for model training, package and deployment in Kubernetes https://danielfrg.com/blog/2018/10/model-management-polyaxon-argo-seldon/ 7 comments
- Getting Better at Machine Learning | by Robert Chang | Medium https://medium.com/@rchang/getting-better-at-machine-learning-16b4dd913a1f 5 comments
- Always start with a stupid model, no exceptions. | by Emmanuel Ameisen | Insight https://blog.insightdatascience.com/always-start-with-a-stupid-model-no-exceptions-3a22314b9aaa 3 comments
- GitHub - alirezadir/Production-Level-Deep-Learning: A guideline for building practical production-level deep learning systems to be deployed in real world applications. https://github.com/alirezadir/Production-Level-Deep-Learning 3 comments
- GitHub - visenger/awesome-mlops: A curated list of references for MLOps https://github.com/visenger/awesome-mlops 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
- GitHub - 1duo/awesome-ai-infrastructures: Infrastructures™ for Machine Learning Training/Inference in Production. https://github.com/1duo/awesome-ai-infrastructures 1 comment
- Mobile Machine Learning 101: Glossary | by Jameson Toole | Medium https://heartbeat.fritz.ai/mobile-machine-learning-101-glossary-7a4ee36e0a1a 0 comments
- We're still in the steam-powered days of machine learning https://vicki.substack.com/p/were-still-in-the-steam-powered-days 0 comments
- Building Production Machine Learning Systems | by Manu Suryavansh | Heartbeat https://heartbeat.fritz.ai/building-production-machine-learning-systems-7eda2fda0cdf 0 comments
- 12 Amazing Deep Learning Breakthroughs of 2017 https://www.forbes.com/sites/mariyayao/2018/02/05/12-amazing-deep-learning-breakthroughs-of-2017/#7983dc6965db 0 comments
- Uber Data Science Interview. The goal of Acing AI is to learn about… | by Vimarsh Karbhari | Acing AI | Medium https://medium.com/acing-ai/uber-ai-interview-questions-acing-the-ai-interview-9532794bc057 0 comments
- ML: Time to Embrace Version Control | A learning journal https://lpalmieri.com/posts/2018-09-14-machine-learning-version-control-is-all-you-need/ 0 comments
- The Rise of the Model Servers. New Tools for Deploying Machine… | by Alex Vikati | Medium https://medium.com/@vikati/the-rise-of-the-model-servers-9395522b6c58 0 comments
- How to Deploy Machine Learning Models https://christophergs.github.io/machine%20learning/2019/03/17/how-to-deploy-machine-learning-models/ 0 comments
- Most impactful AI trends of 2018: the rise of ML Engineering | by Emmanuel Ameisen | Medium https://medium.com/@emmanuelameisen/most-impactful-a-i-trends-of-2018-the-rise-of-ml-engineering-4b1c704f263c 0 comments
- How to Deploy Machine Learning Models A Guide | by Christopher Samiullah | Medium https://medium.com/@christopher.samiullah/how-to-deploy-machine-learning-models-4b8b98120ffe 0 comments
- Infrastructure 3.0: Building blocks for the AI revolution | VentureBeat https://venturebeat.com/2017/11/28/infrastructure-3-0-building-blocks-for-the-ai-revolution/ 0 comments