A popular dataset that we haven't talked much about yet is the Olivetti faces dataset.

The Olivetti face dataset was collected in 1990 by AT&T Laboratories Cambridge. The dataset comprises facial images of 40 distinct subjects, taken at different times and under different lighting conditions. In addition, subjects varied their facial expressions (open/closed eyes, smiling/not smiling) and their facial details (glasses/no glasses).

Images were then quantized into 256 grayscale levels and stored as unsigned 8-bit integers. Because there are 40 distinct subjects, the dataset comes with 40 distinct target labels. Recognizing faces thus constitutes an example of a multiclass classification task.