June 2018
Intermediate to advanced
248 pages
5h 27m
English
Content preview from Mastering Numerical Computing with NumPy
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Summary
In this chapter, you explored the performance of different configurations when you perform compute-intensive linear algebra operations.
Benchmarking is a serious business, and you at least have the basic skills now to run benchmarks. The material you have studied in this chapter is nowhere near complete, but it gave you an idea where to start, and you can definitely improve on many things.
One thing you can look at is how performance metrics behave when you increase the size of vectors and matrices gradually. Ideally, you'll need more powerful hardware, but t2.micro instances are free in most cases or very cheap to provision.
As you will need to handle more compute-intensive workloads, it's important to understand what your options ...
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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.