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Cifar10

Implement Image classification algorithm by applying Principal component analysis

The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images.

Task: Predict correct class for every image in the test dataset

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Implement Image classification algorithm by applying Principal component analysis

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