Object Detection with Amazon Sagemaker
98 ratings

7,371 already enrolled
Prepare data for Sagemaker Object Detection.
Train a model using Sagemaker.
Deploy a trained model using Sagemaker.
98 ratings
7,371 already enrolled
Prepare data for Sagemaker Object Detection.
Train a model using Sagemaker.
Deploy a trained model using Sagemaker.
Please note: You will need an AWS account to complete this course. Your AWS account will be charged as per your usage. Please make sure that you are able to access Sagemaker within your AWS account. If your AWS account is new, you may need to ask AWS support for access to certain resources. You should be familiar with python programming, and AWS before starting this hands on project. We use a Sagemaker P type instance in this project, and if you don't have access to this instance type, please contact AWS support and request access. In this 2-hour long project-based course, you will learn how to train and deploy an object detector using Amazon Sagemaker. Sagemaker provides a number of machine learning algorithms ready to be used for solving a number of tasks. We will use the SSD Object Detection algorithm from Sagemaker to create, train and deploy a model that will be able to localize faces of dogs and cats from the popular IIIT-Oxford Pets Dataset. Since this is a practical, project-based course, we will not dive in the theory behind deep learning based SSD or Object Detection, but will focus purely on training and deploying a model with Sagemaker. You will also need to have some experience with Amazon Web Services (AWS). Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Deep Learning
Machine Learning
sagemaker
Object Detection
Computer Vision
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Introduction
Annotations
Visualize the Data
Sagemaker Setup
Preparing the Data
Uploading Data to S3
Sagemaker Estimator
Data Channels and Model Training
Deploying the Model
Inference and Deleting the Endpoint
Your workspace is a cloud desktop right in your browser, no download required
In a split-screen video, your instructor guides you step-by-step
by MA
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YouTube : https://bit.ly/2PBEung
by SC
Sep 25, 2020Great project. Very thorough and lots of useful tips and tricks. Thank you for sharing this!
by MM
Oct 12, 2020Perfect experience, but a lot of learning still required.
by VS
Jun 21, 2020Good project to get started with AWS Sagemaker, all the steps involved are clearly explained.
By purchasing a Guided Project, you'll get everything you need to complete the Guided Project including access to a cloud desktop workspace through your web browser that contains the files and software you need to get started, plus step-by-step video instruction from a subject matter expert.
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At the top of the page, you can press on the experience level for this Guided Project to view any knowledge prerequisites. For every level of Guided Project, your instructor will walk you through step-by-step.
Yes, everything you need to complete your Guided Project will be available in a cloud desktop that is available in your browser.
You'll learn by doing through completing tasks in a split-screen environment directly in your browser. On the left side of the screen, you'll complete the task in your workspace. On the right side of the screen, you'll watch an instructor walk you through the project, step-by-step.
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