Table of Contents
Preface
Section 1: Framework for Building Machine Learning Models
Chapter 1: Fundamentals of an MLOps Workflow
The evolution of infrastructure and software development
The rise of machine learning and deep learning5
The end of Moore's law7
AI-centric applications7
Software development evolution8
Traditional software development challenges
Trends of ML adoption in software development
Understanding MLOps
Concepts and workflow of MLOps
Discussing a use case 17
Summary
Chapter 2: Characterizing Your Machine Learning Problem
The ML solution development process
Types of ML models
Learning models30
Hybrid models31
Statistical models 34
HITL models36
Structuring your MLOps
Small data ops39
Big data ops40
Hybrid MLOps41
Large-scale ...
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