Overview

• Training Set: 50,000 training images & labels
• Test Set: 10,000 test images & labels
• Color images

Data Format

• Each 32 x 32 pixel single digit image is represented as a 32 x 32 array, with color (3 channel) values. ranging from 0 - 255.
• With 60,000 images, each with 3 color channels sized 32 x 32 results in a 4D array:
• (60,000, 32, 32, 3)
• Classes
• 10 different objects
• airplane, automobile, bird, cat, deer, dog, frog, horse, ship, truck
• Labels
• List of numbers ranging from 0 - 9.

Documentation

CIFAR-10 and CIFAR-100 datasets

aquatic mammals beaver, dolphin, otter, seal, whale fish aquarium fish, flatfish, ray, shark, trout flowers orchids, poppies, roses, sunflowers, tulips food containers bottles, bowls, cans, cups, plates fruit and vegetables apples, mushrooms, oranges, pears, sweet peppers household electrical devices clock, computer keyboard, lamp, telephone, television household furniture bed, chair, couch,

www.cs.toronto.edu

TensorFlow

TF MNIST Dataset

Distributed Training with CIFAR-10 Dataset

Module: tf.keras.datasets.cifar10 | TensorFlow Core v2.4.1

CIFAR10 small images classification dataset.

www.tensorflow.org