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



Course info



Description
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.
Section Introduction Transcripts
Course Overview
Hi everyone. My name is Jorge Vasquez, and welcome to my course, Build, Train, and Deploy Machine Learning Models with AWS SageMaker. AWS SageMaker is a fully managed machine learning service, and it's a great place to start if you want to quickly get machine learning into your applications. In this course, you're going to learn the skills you need to create machine learning models in AWS SageMaker and to integrate them into your applications. Some of the major topics that we will cover include building and training machine learning models in AWS SageMaker, deploying trained models to AWS SageMaker hosting services, building REST APIs for integrating deployed models with external applications using AWS API Gateway and AWS Lambda, managing security and scalability in AWS SageMaker. By the end of this course, you'll be ready to create machine learning models in AWS SageMaker for your own use cases so you can integrate them with your own applications. Before beginning the course, you should be familiar with machine learning basic concepts, deep learning, and convolutional neural network concepts, Python 3 programming using Jupyter Notebooks, using TensorFlow, and Apache MXNet. I hope you'll join me on this journey to learn AWS SageMaker with the Build, Train, and Deploy Machine Learning Models with AWS SageMaker course, at Pluralsight.