November 2021
Intermediate to advanced
276 pages
5h 59m
English
Content preview from Machine Learning Engineering with Python
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Chapter 2: The Machine Learning Development Process
In this chapter, we will define how the work for any successful Machine Learning (ML) software engineering project can be divided up. Basically, we will answer the question of how do you actually organize the doing of a successful ML project? We will not only discuss the process and workflow, but we will also set up the tools you will need for each stage of the process and highlight some important best practices with real ML code examples.
Specifically, this chapter will cover the concept of a discover, play, develop, deploy workflow for your ML projects, appropriate development tooling and their configuration and integration for a successful project. We will also cover version control strategies ...
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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.