CIFAR-10 is a widely used dataset for image classification tasks that consists of 50,000 32x32 colour images in 10 classes. The classes include common objects such as airplanes, cars, birds, cats, deer, dogs, frogs, horses, ships, and trucks. The task is to train a neural network to correctly classify these images into their respective classes. In this project, we will build a neural network model on training dataset and evaluate it on test set.
riyadodthi/CIFAR10_Image_Classification
CIFAR10 Image classification using Deep Learning
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