May 2019
Beginner to intermediate
288 pages
9h 1m
English
book
Machine Learning in Production: Developing and Optimizing Data Science Workflows and Applications
by Andrew Kelleher, Adam Kelleher
Content preview from Machine Learning in Production: Developing and Optimizing Data Science Workflows and Applications
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III. Bottlenecks and Optimizations
Chapter 15, “Hardware Fundamentals,” runs through basic bottlenecks in hardware and includes a brief discussion of the components that make up modern computers.
In Chapter 16, “Software Fundamentals,” we discuss some fundamentals of software design as it relates to quickly and reliably processing data. We’ll take a look at IO eflciency as well as guarantees related to consistency.
Chapter 17, “Software Architecture,” contains a higher-level overview of architectural patterns used in distributed systems.
Chapter 18, “The CAP Theorem,” goes into the trade-offs between availability, consistency, and partition tolerance.
Finally, Chapter 19, “Logical Network Topological Nodes,” provides a toolkit. It describes ...
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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.
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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.