# MNIST Digits With Keras

## Imports

These are the parts that will make up the model.

### The Sequential Model

The Keras Sequential Model is a stack of layers that will make up the neural network.

from keras.models import Sequential


### The Dense Layers

The Keras Dense layer is a densely-connected layer within our neural network.

from keras.layers.core import Activation


### Activation

The Activation represents the activation function for each layer (e.g. relu).

from keras.layers.core import Activation


To tune the model to the data we'll use the Adam optimizer

from keras.optimizers import Adam


### Categorical Converter

Finally, since our problem is a classification problem (identify which of 10 digits an image represents) I'll import the Keras to_categorical function to enable classification of our data.

from keras.utils import np_utils


The MNIST dataset is made up of human-classified hand-written digits. Keras includes it as part of their installation so we can load it directly from keras.

from keras.datasets import mnist


We're going to use numpy to reshape the data.

import numpy


To make our output the same every time, I'll set the random seed to April 28, 2018 as a string of digits.

numpy.random.seed(4282018)