August 2022
Intermediate to advanced
352 pages
11h 36m
English
Content preview from Effective Data Science InfrastructureBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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4 Scaling with the compute layer
This chapter covers
- Designing scalable infrastructure that allows data scientists to handle computationally demanding projects
- Choosing a cloud-based compute layer that matches your needs
- Configuring and using compute layers in Metaflow
- Developing robust workflows that handle failures gracefully
What are the most fundamental building blocks of all data science projects? First, by definition, data science projects use data. At least small amounts of data are needed by all machine learning and data science projects. Second, the science part of data science implies that we don’t merely collect data but we use it for something, that is, we compute something using data. Correspondingly, data and compute are the two ...
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.