Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Machine Learning Engineering  with Python

You're reading from   Machine Learning Engineering with Python Manage the lifecycle of machine learning models using MLOps with practical examples

Arrow left icon
Product type Paperback
Published in Aug 2023
Publisher Packt
ISBN-13 9781837631964
Length 462 pages
Edition 2nd Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Andrew P. McMahon Andrew P. McMahon
Author Profile Icon Andrew P. McMahon
Andrew P. McMahon
Arrow right icon
View More author details
Toc

Table of Contents (12) Chapters Close

Preface 1. Introduction to ML Engineering 2. The Machine Learning Development Process FREE CHAPTER 3. From Model to Model Factory 4. Packaging Up 5. Deployment Patterns and Tools 6. Scaling Up 7. Deep Learning, Generative AI, and LLMOps 8. Building an Example ML Microservice 9. Building an Extract, Transform, Machine Learning Use Case 10. Other Books You May Enjoy
11. Index

Choosing a style

This section will provide a summary of two coding styles or paradigms, which make use of different organizational principles and capabilities of Python. Whether you write your code in an object-orientated or functional style could just be an aesthetic choice. This choice, however, can also provide other benefits, such as code that is more aligned with the logical elements of your problem, code that is easier to understand, or even more performant code.

In the following sections, we will outline the main principles of each paradigm and allow you to choose for yourself based on your use case.

Object-oriented programming

Object-Oriented Programming (OOP) is a style where the code is organized around, you guessed it, abstract objects with relevant attributes and data instead of around the logical flow of your solution. The subject of OOP is worth a book (or several books!) in itself, so we will focus on the key points that are relevant for our ML engineering journey.

First...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime