December 2018
Intermediate to advanced
764 pages
18h 18m
English
Now that we have learned to build and train the CNN model using MNIST data set with TensorFlow and Keras, let us repeat the exercise with CIFAR10 dataset.
The CIFAR-10 dataset consists of 60,000 RGB color images of the shape 32x32 pixels. The images are equally divided into 10 different categories or classes: airplane, automobile, bird, cat, deer, dog, frog, horse, ship, and truck. CIFAR-10 and CIFAR-100 are subsets of a large image dataset comprising of 80 million images. The CIFAR data sets were collected and labelled by Alex Krizhevsky, Vinod Nair, and Geoffrey Hinton. The numbers 10 and 100 represent the number of classes of images.
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