Model Architecture:
The model is a sequential model in TensorFlow/Keras.
Input Layer: A Flatten layer that transforms the input images of size (28, 28) into a flat vector.
Hidden Layers: The model has two fully connected hidden layers with 512 and 256 neurons, respectively, using the ReLU activation function.
Output Layer: A fully connected layer with 10 neurons using the Softmax activation function for the task of classifying into 10 clothing categories in Fashion MNIST.
Model Statistics:
Loss on the test dataset: 0.4328601062297821.
Accuracy on the test dataset: 0.8863000273704529.
I'm still learning, in this model I'm trying to use validation set
