Summary
In this chapter, we learned about multiple practical aspects that we need to take into consideration when building CNN models: batch normalization, data augmentation, explaining the outcomes using CAMs, and some scenarios that you need to be aware of when moving a model to production.
In the next chapter, we will switch gears and learn about the fundamentals of object detection: where we will not only identify the classes corresponding to objects in an image but also draw a bounding box around the location of the object.
