Build, Train, and Deploy Machine Learning Models with Amazon SageMaker

by Jorge Vasquez

In this course, you are going to learn the skills you need to build, train, and deploy machine learning models in Amazon SageMaker, including how to create REST APIs to integrate them into your applications for solving real-world problems.

What you'll learn

A fully managed machine learning service is a great place to start if you want to quickly get machine learning into your applications. In this course, Build, Train, and Deploy Machine Learning Models with Amazon SageMaker, you will gain the ability to create machine learning models in Amazon SageMaker and to integrate them into your applications. First, you’ll learn the basics and how to set up SageMaker. Next, you’ll discover how to build, train, and deploy models applied to Image Classification for breast cancer detection and how to integrate them into a REST API. Finally, you will even discover how to manage security and scalability in Amazon SageMaker. When you’re finished with this course, you will have a foundational understanding of Amazon SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

Table of contents

Course Overview
1min

About the author

Jorge is a passionate person who loves building quality software that allows people to solve their problems. He also loves to teach, that's why he works several years ago teaching programming and software development to university students. He has experience developing highly performant backend systems with Java and Node.js, building ETL processes with Python and Scala and working with cloud platforms such as Amazon Web Services. His current areas of interest include Deep Neural Networks, Comput... more

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