Fashion MNIST is a dataset containing 70,000(60,000 examples and test set 10,000) 28x28 images. Each image corresponds to a label from a list of classes listed below:
| Label | Description |
|---|---|
| 0 | T-shirt/top |
| 1 | Trouser |
| 2 | Pullover |
| 3 | Dress |
| 4 | Coat |
| 5 | Sandal |
| 6 | Shirt |
| 7 | Sneaker |
| 8 | Bag |
| 9 | Ankle boot |
This project creates a convolutional neural network that is trained and evaluated on the provided FashionMNIST dataset.
A confusion matrix is also built to evaluate the performance of the trained network on a test dataset to provide a clear indication of the performance of a model prediction on a class basis.