hands-on lab

Forecast Flight Delays with Amazon SageMaker

Difficulty: Beginner

Duration: Up to 1 hour and 30 minutes

Students: 1,377

Rating: 4.7/5

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Description

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.

Lab Objectives

Upon completion of this lab you will be able to:

Train models using built-in SageMaker algorithms
Create SageMaker models
Deploy SageMaker endpoints to get real-time inferences from your models
Explain different machine learning concepts such as model types, data encoding, and training and test sets