May 2020
Intermediate to advanced
404 pages
10h 52m
English
Content preview from Hands-On Python Deep Learning for the Web
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Deployment and monitoring
After a machine learning model is built, it is merged with the other components of an application and is taken into production. This phase is referred to as model deployment. The true performance of the developed ML model is evaluated after it is deployed into real systems. This phase also involves thorough monitoring of the model to figure out the areas where the model is not performing well and which aspects of the model can be improved further. Monitoring is extremely crucial as it provides the means to enhance the model's performance and thereby enhance the performance of the overall application.
So, that was a kind of a primer of the most important terminologies/concepts required for an ML project.
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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.