Part 1:Debugging for Machine Learning Modeling

In this part of the book, we will delve into the different aspects of machine learning development that extend beyond traditional paradigms. The first chapter illuminates the nuances between conventional code debugging and the specialized realm of machine learning debugging, emphasizing that the challenges in ML transcend mere code errors. The next chapter provides a comprehensive overview of the machine learning life cycle, highlighting the role of modularization in streamlining and enhancing model development. Finally, we will underscore the importance of model debugging in the pursuit of Responsible AI, emphasizing its role in ensuring ethical, transparent, and effective machine learning solutions.

This part has the following chapters:

• Chapter 1, Beyond Code Debugging
• Chapter 2, Machine Learning Life Cycle
• Chapter 3, Debugging toward Responsible AI

...