Rolling in the deep

You have been asked by the local police department to produce a Deep Learning model for license plate reading.

Your input data are images of digits, 28 pixels wide and 28 pixels tall, each with a label stating which of the 10 possible digits is present on the picture.

The Sequential() model is already loaded, which you will use to build a Deep Neural Network using the following layers:

Conv2D() - 2D convolutional layer
MaxPooling2D() - pooling layer
Flatten() - flattening layer
Dense() - fully connected layer

Initialize the model and set a 2D convolutional layer with 64 filters of size 3x3 at the input.
Add a MaxPooling2D() layer, with default parameters, followed by a flattening layer, to reshape the signal from a 2-dimensional to a 1-dimensional format.
Add a fully connected Dense() layer with a softmax activation function and 10 neurons for 10 target classes present in our training set.
Compile the model.

Exercise

Rolling in the deep

Instructions