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Open-Sourcing Metaflow, a Human-Centric Framework for Data Science

The Netflix TechBlog

On the other hand, very few data scientists feel strongly about the nature of the data warehouse, the compute platform that trains and scores their models, or the workflow scheduler. In this hypothetical example, the flow trains two versions of a model in parallel and chooses the one with the highest score.

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MLOps and DevOps: Why Data Makes It Different

O'Reilly

Cloud-based data warehouses, such as Snowflake , AWS’ portfolio of databases like RDS, Redshift or Aurora , or an S3-based data lake , are a great match to ML use cases since they tend to be much more scalable than traditional databases, both in terms of the data set sizes as well as query patterns. Software Development Layers.

DevOps 138
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Open-Sourcing Metaflow, a Human-Centric Framework for Data Science

The Netflix TechBlog

On the other hand, very few data scientists feel strongly about the nature of the data warehouse, the compute platform that trains and scores their models, or the workflow scheduler. In this hypothetical example, the flow trains two versions of a model in parallel and chooses the one with the highest score.

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The Amazon.com 2010 Shareholder Letter Focusses on Technology.

All Things Distributed

Werner Vogels weblog on building scalable and robust distributed systems. Look inside a current textbook on software architecture, and youll find few patterns that we dont apply at Amazon. The storage systems weve pioneered demonstrate extreme scalability while maintaining tight control over performance, availability, and cost.