Training and saving a Keras model
To deploy a deep learning model in production, you first need a trained model. For that, we've prepared a
Python script called
train.py that performs the following tasks:
- Loading the MNIST dataset containing handwritten digits and their labels
- Defining a small Multilayer Perceptron (MLP) model in Keras
- Training this model on MNIST data and storing the resulting model to the file
If you're interested in the details, click on
train.py in the editor on the right. If you're
ready to go, you can simply run this script by clicking below.
As the script runs, you'll see that
model.h5 gets created in the file tree of your editor window.
That completes the first step. We can now that Keras model with the Skymind Intelligence Layer (SKIL).