Table of Contents
Preface
Part 1: What Data-Centric Machine Learning Is and Why We Need It
1
Exploring Data-Centric Machine Learning
Understanding data-centric ML
The origins of data centricity
The components of ML systems
Data is the foundational ingredient
Data-centric versus model-centric ML
Data centricity is a team sport
The importance of quality data in ML
Identifying high-value legal cases with natural language processing
Predicting cardiac arrests in emergency calls
Summary
References
2
From Model-Centric to Data-Centric – ML’s Evolution
Exploring why ML development ended up being mostly model-centric
The 1940s to 1970s – the early days
The 1980s to 1990s – the rise of personal computing and the internet
The 2000s – the rise of tech ...
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