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title: Python & TensorFlow Tutorial

# About this tutorial

This tutorial is based on a book I co-authored with Sander Muller and a talk given at PyCon US 2017, “Python and TensorFlow: Get them together”.

It is the first in a series of tutorials showing how to build real-world applications that use TensorFlow, starting from the basics. We’ll cover how to write, train, and deploy TensorFlow models in Python, and how to deploy these models to production. This tutorial will show you how to build a tiny app that automatically recommends music to you, based on your listening habits.

We recommend you read through the [Python and TensorFlow reference](/PythonTensorFlow/index.html) before starting the tutorial.

For this tutorial, you’ll use the pre-built image that we have uploaded on Google Cloud Platform. If you don’t have a running instance, you can download the instance from our [Docker Hub]( site.

# How to build this tutorial

First, create an instance on Google Cloud Platform and download the project tarball. Then, you need to install the required dependencies. See the [Dockerfile]( for more information.

The last step is to run the Dockerfile and create the environment for the tutorial.

See the [environment configuration instructions](#environment-configuration) to make sure that you have configured the environment correctly. 70238732e0

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How to deploy your application

Make sure you have the Dockerfile available for the environment. Copy this file to your Google Cloud Storage bucket and run the Docker command.

“`shell
export PROJECT_ID=1234

docker run –name gcp-tensorflow-tutorial -v $PWD/tutorial

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