Part 5:Advanced Topics in Model Debugging

In the concluding part of this book, we will address some of the most pivotal topics in machine learning. We will begin by explaining differences between correlation and causality, shedding light on their distinct implications in model development. Transitioning to the topic of security and privacy, we will discuss the pressing concerns, challenges, and techniques that ensure our models are both robust and respectful of user data. We will wrap up the book with an explanation of human-in-the -loop machine learning, emphasizing the synergy between human expertise and automated systems, and how this collaboration paves the way for more effective solutions.

This part has the following chapters:

• Chapter 15, Correlation versus Causality
• Chapter 16, Security and Privacy in Machine Learning
• Chapter 17, Human-in-the-Loop Machine Learning

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