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Fashion_MNIST-image-classification-using-CNN-

  • Developed a custom CNN (Convolutional Neural Network) model for classifying the images of the fashion_mnist dataset containing 60,000 training images and 10,000 testing images.
  • This dataset consists of 28 x28 grayscale images from ten different classes of fashion clothes.
  • The different classes are: T-shirt/top, Trouser, Pullover, Dress, Coat, Sandal, Shirt, Sneaker, Bag, Ankle boot.
  • The images are stored in the form of pixels with values ranging from 0 to 255.
  • Accuracy achieved : 93.49%
  • The total number of correctly and incorrectly classified images was also calculated and the figures for the same are: 9349 and 651.