Part 1: What Data-Centric Machine Learning Is and Why We Need It

In this part, we take a deep dive into data-centric machine learning, contrasting it with model-centric approaches. We use real-life examples to illustrate their differences and explore the evolution of AI and ML toward a data-centric perspective. We also dispel the myth of “big data,” highlighting the importance of quality over quantity, and the potential for democratizing ML solutions. Prepare for a fresh perspective on the transformative power of data in ML.

This part has the following chapters:

• Chapter 1, Exploring Data-Centric Machine Learning
• Chapter 2, From Model-Centric to Data-Centric – ML’s Evolution