This page describes how to get started using TensorFlow Enterprise with Notebooks.
In this example, you create a TensorFlow Enterprise instance of Notebooks, open a JupyterLab notebook, and run a classification tutorial on using neural networks with Keras.
Before you beginBefore you can use Notebooks, you must have a Google Cloud project and enable the Notebooks API for that project.
- Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.
In the Google Cloud Console, on the project selector page, select or create a Google Cloud project.
Make sure that billing is enabled for your Cloud project. Learn how to confirm that billing is enabled for your project.
- Enable the Notebooks API.
Create a Notebooks instance
To create a default TensorFlow Enterprise 2.3 Notebooks instance, complete the following steps. To specify properties for your instance, see Create a Notebooks instance with specific properties or go to notebook.new to go directly to the Advanced options instance creation dialog box.
Go to the Notebooks page in the Google Cloud Console.
ClickNew Instance, select TensorFlow Enterprise 2.3, and then select Without GPUs .
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 Notebooks instance:
On the Notebooks page in the Google Cloud Console, click Open JupyterLab to open the notebook.
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 Notebooks.
- Get started using TensorFlow Enterprise with Deep Learning VM.
- Get started using TensorFlow Enterprise with Deep Learning Containers.