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.

Question

Quizplus · Accepted Answer

Deep learning with multiple hidden layers (deep neural networks) is effective for automatically learning complex features, such as those needed for face recognition, from raw image data.

Suppose You Have a Dataset of Images That Are Each