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 beginBefore you can use AI Platform Notebooks, you must have a Google Cloud project and enable the Compute Engine API for that project.
Sign in to your Google Account.
If you don't already have one, sign up for a new account.
In the Cloud Console, on the project selector page, select or create a Cloud project.
Make sure that billing is enabled for your Google Cloud project. Learn how to confirm billing is enabled for your project.
- Enable the Compute Engine API.
Create an AI Platform Notebooks instance
To create a TensorFlow Enterprise AI Platform Notebooks instance, complete these steps:
Go to the AI Platform Notebooks page in the Google Cloud Console.
ClickNew Instance, select TensorFlow Enterprise 1.15, and then select Without GPUs .
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 notebookComplete these steps to open a notebook instance:
On the AI Platform Notebooks page in the Google Cloud Console, click Open JupyterLab to open the notebook.
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:
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.
Click the run buttonto run cells of the tutorial.
- Learn more about AI Platform Notebooks.
- Get started using TensorFlow Enterprise with Deep Learning VM.
- Get started using TensorFlow Enterprise with Deep Learning Containers.