The Fashion-MNIST clothing classification problem is a new standard dataset used to classify clothing's with deep learning
For this model, I am going to use the Fashion MNIST dataset that consists of Zalando’s article images which is a set of 28x28 greyscale images of clothes, a drop-in replacement for the MNIST dataset. Here, you’ll learn to build your own neural network.Fashion MNIST dataset consists of 70,000 grayscale images and 10 classes.You can see here: https://github.com/zalandoresearch/fashion-mnist#labels
As with MNIST, each image is 28x28 which is a total of 784 pixels, and there are 10 classes. You should include at least one hidden layer. We suggest you use ReLU activations for the layers and to return the logits or log-softmax from the forward pass. It’s up to you how many layers you add and the size of those layers.
Can Check On Kaggle: https://www.kaggle.com/afafathar3007/fashionmnist-model-prediction