The following labs will give you hands-on experience with a number of the topics discussed during AWS Innovate.
ℹ️ You will run these lab in your own AWS account. Please follow directions at the end of the labs to remove resources to minimize costs.
These labs will remain available after AWS Innovate. You can do them at any time, even after AWS Innovate.
This lab demonstrates how to use Amazon SageMaker reinforement learning to 'learn' how to to play the Breakout video game.
This lab shows you how, using AWS, you can parallelize the training of your reinforcement learning algorithms to get insanely fast turnaround times & results for your reinforcement learning experiments.
Duration: Approximately 30 minutes
Losing customers is costly for any business. Identifying unhappy customers early on gives you a chance to offer them incentives to stay. This notebook describes using machine learning (ML) for the automated identification of unhappy customers, also known as customer churn prediction.
Duration: Approximately 30 minutes
In this lab, you will work on the different aspects of the ML workflow to build, train, and deploy a model using all the capabilities of Amazon SageMaker including the ones announced at re:Invent 2019. You will use the Amazon SageMaker to build, train & debug models with Amazon SageMaker Debugger, and deploy & monitor with Amazon SageMaker Model Monitor.
Duration: Approximately 90 minutes
In this lab, you will be building a contact center using Amazon Connect and integrating with Amazon Lex. Amazon Lex interprets dual-tone multi-frequency signaling (DTMF) digits entered on a keypad. It matches the intent based on that input in the same way it matches the intent when you speak an utterance. This provides for greater flexibility for customers to interact with your contact center.
Duration: Approximately 1 hour
Learn how to create a Reinforcement Learning model for AWS DeepRacer and participate in the DeepRacer League!
Duration: Approximately 1 hour