Practical Machine Learning with AWS: Process, Build, Deploy, and Productionize Your Models Using AWS

© Himanshu Singh 2021

H. SinghPractical Machine Learning with AWS https://doi.org/10.1007/978-1-4842-6222-1_9

9. Making an End-to-End Pipeline in SageMaker

Himanshu Singh¹  

(1)

ALLAHABAD, Uttar Pradesh, India

 

In this chapter, we will see how we can make an end-to-end pipeline of an entire machine learning process. We can use a combination of AWS services to automate the entire process of machine learning. All the processes that we have seen in the previous chapters, from the data processing steps to the endpoint generation, can be automated and then be run directly with a click of a button. The only thing we need to change is the dataset, but the process remains the same. Let’s see how we can automate what we did on the Big Mart dataset in the previous ...