To create a classifier to classify fashion clothing into 10 categories based on Fashion MNIST dataset
The given solutions in this project are only for reference purpose.
https://www.kaggle.com/zalando-research/fashionmnist
Fashion-MNIST is a dataset of Zalando's article images—consisting of a training set of 60,000 examples and a test set of 10,000 examples. Each example is a 28x28 grayscale image, associated with a label from 10 classes
Each image is 28 pixels in height and 28 pixels in width, for a total of 784 pixels in total. Each pixel has a single pixel-value associated with it, indicating the lightness or darkness of that pixel, with higher numbers meaning darker. This pixel-value is an integer between 0 and 255. The training and test data sets have 785 columns. The first column consists of the class labels (see above), and represents the article of clothing. The rest of the columns contain the pixel-values of the associated image.
Each training and test example is assigned to one of the following labels:
0 T-shirt/top
1 Trouser
2 Pullover
3 Dress
4 Coat
5 Sandal
6 Shirt
7 Sneaker
8 Bag
9 Ankle boot
Original dataset was downloaded from https://github.com/zalandoresearch/fashion-mnist
Dataset was converted to CSV with this script: https://pjreddie.com/projects/mnist-in-csv/