001-Course Overview

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

002-Introduction

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

003-Course Scenario

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

004-Overview of How the Sample REST API for Breast Cancer Detection Should Work

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

005-Introduction to AWS SageMaker

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

006-Setting up AWS SageMaker

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

007-Summary

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

008-Introduction

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

009-SageMaker Notebook Instances

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

010-Creating a Notebook Instance

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

011-Overview of the Image Classification Built in Algorithm

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

012-Obtaining Exploring and Preprocessing Histopathology Images

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

013-Configuring the Image Classification Algorithm Using the Low level AWS SDK for Python

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

014-Configuring the Image Classification Algorithm Using the High level SageMaker Python Library

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

015-Overview of Using Tensorflow in SageMaker

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

016-Converting Images to the TFRecord Format

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

017-Configuring a Tensorflow Estimator Using the High level SageMaker Python Library

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

018-Overview of Using Apache MXNet in SageMaker

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

019-Configuring a MXNet Estimator Using the High level SageMaker Python Library

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

020-Summary

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

021-Introduction

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

022-Overview of Creating Training Jobs in SageMaker

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

023-Creating and Monitoring a Training Job for the Built in Image Classification Algorithm Using the Low level AWS SDK for Python

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

024-Creating and Monitoring a Training Job for the Built in Image Classification Algorithm Using the High level SageMaker Python Library-git

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

025-Creating and Monitoring a Training Job for the Custom Tensorflow Algorithm Using the High level SageMaker Python Library

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

026-Creating and Monitoring a Training Job for the Custom MXnet Algorithm Using the High level SageMaker Python Library

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

027-Overview of Automatic Hyperparameter Optimization

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

028-Creating and Monitoring a Tuning Job for the Built in Image Classification Algorithm Using the Low level AWS SDK for Python

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

029-Creating and Monitoring a Tuning Job for the Built in Image Classification Algorithm Using the High level SageMaker Python Library

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

030-Creating and Monitoring a Tuning Job for the Custom Tensorflow Algorithm Using the High level SageMaker Python Library

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

031-Creating and Monitoring a Tuning Job for the Custom MXnet Algorithm Using the High level SageMaker Python Library

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

032-Summary

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

033-Introduction

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

034-Overview of Deploying and Testing Machine Learning Models in AWS SageMaker Hosting Services

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

035-Deploying and Testing the Trained Model Based on the Built in Image Classification Algorithm Using the Low level AWS SDK for Python

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

036-Deploying and Testing the Trained Model Based on the Built in Image Classification Algorithm Using the High level SageMaker Python Library

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

037-Deploying and Testing the Trained Model Based on a Custom Tensorflow Algorithm Using the High level SageMaker Python Library

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

038-Deploying and Testing the Trained Model Based on a Custom Mxnet Algorithm Using the High level SageMaker Python Library

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

039-Overview of Integrating Endpoints with AWS API Gateway and AWS Lambda

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

040-Integrating an AWS SageMaker Endpoint with AWS API Gateway and AWS Lambda

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

041-Summary

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

042-Introduction

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

043-Overview of Managing Authentication and Access Control Using IAM Policies

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

044-Configuring Access Control to Notebook Instances

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

045-Overview of Monitoring and Troubleshooting Deployed Models with AWS CloudWatch

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

046-Analyzing Endpoint Metrics and Logs with AWS CloudWatch

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

047-Overview of Configuring Automatic Scaling for AWS SageMaker Endpoints

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

048-Configuring Automatic Scaling for an AWS SageMaker Endpoint Using the AWS Console

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

049-Summary

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.

Exercise files.ZIP

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 AWS SageMaker, you will gain the ability to create machine learning models in AWS 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 AWS SageMaker. When you're finished with this course, you will have a foundational understanding of AWS SageMaker that will help you immensely as you move forward to create your own machine-learning-enabled applications applied to different real-life scenarios.