Part 3:Low-Bug Machine Learning Development and Deployment

With this part of the book, we will provide the essential practices to ensure the robustness and reliability of machine learning models, especially in production. We will start with the adoption of Test-Driven Development, illustrating its crucial role in mitigating risks during model development. Subsequently, we will delve into the testing techniques and the significance of model monitoring, ensuring that our models remain dependable when deployed. We will then explain techniques and challenges in achieving reproducibility in machine learning through code, data, and model versioning. We will conclude this part by addressing the challenges of data and concept drifts to have reliable models in production.

This part has the following chapters:

• Chapter 8, Controlling Risks Using Test-Driven Development
• Chapter 9, Testing and Debugging for Production
• Chapter 10, Versioning and Reproducible Machine Learning Modeling...