Part 3: Model Evaluation Metrics and Putting Your Model into Production

In this part, you will expand on the model metrics used in Part 2 and measure how well a model is working for your dataset and how to adjust modeling parameters to improve the measurements, including metrics for classification models. You will learn how to use pipelines to manage feature engineering tasks. Lastly, you will gain experience in deploying an XGBoost model into a production environment.

This part contains the following chapters:

• Chapter 11, Metrics for Model Evaluations and Comparisons
• Chapter 12, Managing a Feature Engineering Pipeline in Training and Inference
• Chapter 13, Deploying Your XGBoost Model