Using TensorFlow Enterprise with AI Platform Notebooks

This page describes how to get started using TensorFlow Enterprise with AI Platform Notebooks.

In this example, you create a TensorFlow Enterprise instance of AI Platform Notebooks, open a JupyterLab notebook, and run a classification tutorial on using neural networks with Keras.

Before you begin

Before you can use AI Platform Notebooks, you must have a Google Cloud project and enable the AI Platform Notebooks API for that project.
  1. Sign in to your Google Account.

    If you don't already have one, sign up for a new account.

  2. In the Cloud Console, on the project selector page, select or create a Cloud project.

    Go to the project selector page

  3. Make sure that billing is enabled for your Google Cloud project. Learn how to confirm billing is enabled for your project.

  4. Enable the AI Platform Notebooks API.

    Enable the API

Create an AI Platform Notebooks instance

To create a TensorFlow Enterprise AI Platform Notebooks instance, complete these steps:

  1. Go to the AI Platform Notebooks page in the Google Cloud Console.

    Go to the AI Platform Notebooks page

  2. Click New Instance, select TensorFlow Enterprise 1.15, and then select Without GPUs .

  3. Click Create.

  4. AI Platform Notebooks creates a new instance based on your selected framework. An Open JupyterLab link becomes active when it's ready to use.

Open the notebook

Complete these steps to open a notebook instance:
  1. On the AI Platform Notebooks page in the Google Cloud Console, click Open JupyterLab to open the notebook.

  2. AI Platform Notebooks opens your notebook.

Run a classification tutorial in your notebook instance

Complete these steps to try out your new notebook by running a classification tutorial:

  1. In your JupyterLab notebook, on the left, double-click the tutorials folder to open it, and navigate to and open tutorials/keras/basic_classification.ipynb.

  2. Click the run button to run cells of the tutorial.

What's next