Part 3: Applying Active Machine Learning to Real-World Projects

Part 3 concludes the exploration of active machine learning (ML) by equipping readers with the knowledge to not only understand advanced active ML methods but also to apply them effectively in real-world scenarios. Through the advanced tools discussed in these chapters, practitioners will be prepared to tackle complex challenges, drive innovation, and achieve significant improvements in their ML projects. Whether it’s through refining evaluation practices or leveraging powerful software, this section aims to inspire and guide readers toward mastery of the art and science of active ML.

This part includes the following chapters:

• Chapter 6, Evaluating and Enhancing Efficiency
• Chapter 7, Utilizing Tools and Packages for Active ML