Your team needs to build a model that predicts whether images contain a driver`s license, passport, or credit card. The data engineering team already built the pipeline and generated a dataset composed of 10,000 images with driver`s licenses, 1,000 images with passports, and 1,000 images with credit cards. You now have to train a model with the following label map: [`˜drivers_license`, `˜passport`, `˜credit_card`]. Which loss function should you use? 

Answer options:

A. Categorical hinge
B. Binary cross-entropy
C. Categorical cross-entropy
D. Sparse categorical cross-entropy

D

se sparse_categorical_crossentropy. Examples for above 3-class classification problem: [1] , [2], [3] Reference: https://stats.stackexchange.com/questions/326065/cross-entropy-vs-sparse-cross-entropy-when-to-use-one-over-the-other