Chapter 6 - Practical Aspects of Image Classification

1. How are class activation maps obtained?
   Refer to the 8 steps provided in the Generating CAMs section

2. How do batch normalization and data augmentation help when training a model?
   They help reduce over-fitting

3. What are the common reasons why a CNN model overfits?
   No batch normalization, data augmentation, dropout

4. What are the various scenarios where the CNN model works with training and validation data at the data scientists' end but not in the real world?
   Real-world data can have a different distribution from the data used to train and validate the model. Additionally, the model might have over-fitted on training data

5. What are the various scenarios where we leverage OpenCV packages?
   While working in constrained environments, and also when speed to infer is more important