TensorFlow is a popular framework used for machine learning. The Amazon Deep Learning AMI comes bundled with everything you need to start using TensorFlow from development through to production. In this Lab, you will develop, visualize, serve, and consume a TensorFlow machine learning model using the Amazon Deep Learning AMI.

Lab Objectives

Upon completion of this lab you will be able to:

• Create machine learning models in TensorFlow
• Visualize TensorFlow graphs and the learning process in TensorBoard
• Serve trained TensorFlow models with TensorFlow Serving
• Create clients that consume served TensorFlow models, all with the Amazon Deep Learning AMI

Lab Prerequisites

You should be familiar with:

• Working at the Linux command line
• The Python programming language
• Some linear algebra knowledge is beneficial (basic vector and matrix operations)
• Basic understanding of neural networks is beneficial, but not required

Lab Environment

Before completing the lab instructions, the environment will look as follows:

After completing the lab instructions, the environment should look similar to:

Updates

December 2nd, 2022 - Updated lab to use EC2 Instance Connect and added a check

January 17th, 2022 - Improved instructions for establishing an SSH tunnel with PuTTY for Windows users

January 12th, 2022 - Updated and added SSH tunnel instructions

January 3rd, 2022 - Updated to use Python 3

August 1st, 2021 - Fixed typo in lab instructions

December 7th. 2020 - Updated instructions to address an issue that prevented a lab step from being able to be completed successfully

April 15th, 2020 - Updated instructions to provide for a more streamlined lab experience

January 10th, 2019 - Added a validation lab Step to check the work you perform in the lab