Summary
In this chapter, you learned about the importance of avoiding drift in your machine learning models, and how you can benefit from the concepts you learned in previous chapters such as model versioning and monitoring to do so. You also practiced with two libraries for drift detection in Python: alibi_detect and evidently. Using these or similar libraries will help you to eliminate drift in your models and have reliable models in production.
In the next chapter, you will learn about different types of deep neural network models and how to use PyTorch to develop reliable deep learning models.
