Suppose You Have a Dataset of Images That Are Each

Multiple Choice

Suppose you have a dataset of images that are each labeled as to whether or not they contain a human face. To create a neural network that recognizes human faces in images using this labeled dataset, what approach would likely be the most effective?

A) Use K-means Clustering to detect faces in the pixels.
B) Use feature engineering to add features for eyes, noses, and mouths to the input data.
C) Use deep learning by creating a neural network with multiple hidden layers to automatically detect features of faces.
D) Build a neural network with an input layer of pixels, a hidden layer, and an output layer with two categories.