Installing Keras on Google Cloud is very simple. First, we can install Google Cloud (for the downloadable file, refer to https://cloud.google.com/sdk/), a command-line interface for Google Cloud Platform; then we can use CloudML, a managed service that enables us to easily build machine, learning models with TensorFlow. Before using Keras, let's use Google Cloud with TensorFlow to train an MNIST example available on GitHub. The code is local and training happens in the cloud:
In the following screenshot, you can see how to run a training session:
We can use TensorBoard to show how cross-entropy decreases across iterations:
In the next screenshot, we see the graph of cross-entropy:
Now, if we want to use Keras on the top of TensorFlow, we simply download the Keras source from PyPI (for the downloadable file, refer to https://pypi.Python.org/pypi...
