The hands-on lab is part of this learning path
Introduction to Machine Learning on AWS
Ready for the real environment experience?
Neural networks have been used for many applications throughout the deep learning revolution. In this Lab, you will use the AWS Deep Learning AMI using a GPU instance (p2.xlarge). You will perform neural style transfers - an algorithm for combining the content of one image with the style of another image. This process involves using convolutional neural networks (CNN). The code you will run is implemented in Python using the MXNet deep learning framework. Additionally, you will setup a custom Python script to aggregate GPU performance data and publish it into Amazon CloudWatch. You will then be able to examine the performance and cost associated with the CNN as it runs.
Upon completion of this Lab you will be able to:
- Perform neural style transfers using the AWS Deep Learning AMI
- Publish GPU metrics to Amazon CloudWatch using a Python script
- Examine GPU performance in Amazon CloudWatch
You should be familiar with:
- Working with Linux on the command-line
- Graphics processing unit (GPU) concepts
- Knowledge of the Python programming language is beneficial, but not required
Before completing the Lab instructions, the environment will look as follows:
After completing the Lab instructions, the environment should look similar to:
About the Author
Logan has been involved in software development and research for over eleven years, including six years in the cloud. He is an AWS Certified DevOps Engineer - Professional, MCSE: Cloud Platform and Infrastructure, Google Cloud Certified Associate Cloud Engineer, and Certified Kubernetes Administrator (CKA). He earned his Ph.D. studying design automation and enjoys all things tech.