This lab uses Amazon SageMaker to create a machine learning model that forecasts flight delays for US domestic flights. Amazon SageMaker is a fully-managed service that covers the entire machine learning workflow. The lab does not require any data science or developer experience to complete. You will focus on the easy-to-use SageMaker interface for creating machine learning models using built-in algorithms with relevant concepts explained along the way. You will use US Department of Transportation flight data to train the model that forecasts flight delays. This lab uses SageMaker to create a regression model. Regression models predict a continuous variable, as opposed to a set of classes that are predicted by classification models. You will finish the lab by creating a script that retrieves real-time inference from SageMaker.
Upon completion of this lab you will be able to:
You should be familiar with:
September 1st, 2023 - AWS resolved an issue causing training job validation to fail
July 5th, 2023 - Resolved training job creation issue
July 3rd, 2023 - Updated the instructions and screenshots to reflect the latest UI
December 19th, 2022 - Updated instructions to include new links
November 4th, 2022 - Updated screenshots and instructions to match UI changes
April 16th, 2021 - Moved validation checks to the most relevant lab step for more immediate validation feedback
Logan has been involved in software development and research since 2007 and has been in the cloud since 2012. He is an AWS Certified DevOps Engineer - Professional, AWS Certified Solutions Architect - Professional, Microsoft Certified Azure Solutions Architect Expert, MCSE: Cloud Platform and Infrastructure, Google Cloud Certified Associate Cloud Engineer, Certified Kubernetes Security Specialist (CKS), Certified Kubernetes Administrator (CKA), Certified Kubernetes Application Developer (CKAD), and Certified OpenStack Administrator (COA). He earned his Ph.D. studying design automation and enjoys all things tech.