View profile dispatch - Issue #33: Wizards of Oz, MLOps and Lifecycle Management, Netflix open-sources Metaflow, and more...


nibble dispatch

December 23 · Issue #33 · View online

Curated essays about the future of Data Science. Production Data Science and learning resources for continuous learning. Covers Data Science, Data Engineering, MLOps & DataOps. Curated by people at

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Hello dear reader,
This is our last issue of 2019! While the 2010s have seen the rise (and hype) of applied data science, we hope the next ten years will be about bringing it to maturity.
What’s next? dispatch will resume in 2020. What started as a weekly release is shifting to a more steady pace. While the fast release cycle was perfect for quick iteration, we now want to make sure we can maintain quality while working on other projects.
Our editorial line will stay the same: to help you become a better data practitioner and be prepared for the future of data science. This takes the form of curating relevant industry essays, news about tools and learning resources that will sharpen your technical abilities.
Besides this publication and client work, we’ve been working on an exciting new project: a series of MLOps events in Paris. This aim at bringing more awareness to the field and help practitioners learn from each other. We will be launching the series with Managing the Machine Learning lifecycle with MLflow next January, 16th.
I had a great time preparing these issues, and I hope you enjoyed reading them.
Wishing you the best for 2020,

Wizards of Oz?
Wizards of Oz?
AI update, late 2019 – wizards of Oz
Adapt or Die: why your business strategy is failing your data strategy
MLOps — Data Skeptic 🎙
Enterprise Readiness, MLOps and Lifecycle Management 🎙
Netflix open-sources Metaflow
TensorFlow introduces
Learning resources
Machine Learning Systems design
Monoid in the Category of Endofunctors
End notes
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