Artificial Intelligence Research Intern Interview Questions and Answers

Normalization in deep learning refers to scaling input data to a standard range to improve model performance.

• Normalization helps in speeding up the training process by ensuring that all input features have similar scales.

• Common types of normalization include min-max scaling, z-score normalization, and batch normalization.

• Min-max scaling scales the data to a fixed range, typically between 0 and 1.

• Z-score normalization transforms the data to have a mean of 0 and a standard devi...read more