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Semantic Segmentation with Amazon Sagemaker(으)로 돌아가기

Coursera Project Network의 Semantic Segmentation with Amazon Sagemaker 학습자 리뷰 및 피드백

4.6
별점
79개의 평가

강좌 소개

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 a Semantic Segmentation model 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 semantic segmentation algorithm from Sagemaker to create, train and deploy a model that will be able to segment images of dogs and cats from the popular IIIT-Oxford Pets Dataset into 3 unique pixel values. That is, each pixel of an input image would be classified as either foreground (pet), background (not a pet), or unclassified (transition between foreground and background). Since this is a practical, project-based course, we will not dive in the theory behind deep learning based semantic segmentation, 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)....

최상위 리뷰

AA

2022년 1월 11일

I found the project to be a great step-by-step introduction to using notebooks within sagemaker in order to orchestrate training/deployment jobs!

MA

2021년 3월 7일

Thanks So Much Coursera Learning Platform i Learn lot of Skills from Here, and get start my Business www.facebook.com/MySalesWays

필터링 기준:

Semantic Segmentation with Amazon Sagemaker의 14개 리뷰 중 1~14

교육 기관: Tarun

•

2021년 7월 1일

Some of the critical code is not working now. I think Coursera should achieve the course until things get updated by the instructor.

교육 기관: Alireza A

•

2022년 1월 12일

I found the project to be a great step-by-step introduction to using notebooks within sagemaker in order to orchestrate training/deployment jobs!

교육 기관: Mustafa A

•

2021년 3월 8일

Thanks So Much Coursera Learning Platform i Learn lot of Skills from Here, and get start my Business www.facebook.com/MySalesWays

교육 기관: Mihir I

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2022년 4월 23일

Great ML Project using Amazon Sagemaker !

교육 기관: Enrique A M

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2021년 10월 26일

That s very incredible course, thanks

교육 기관: Devidas K

•

2020년 5월 19일

It was Wonderful learning Experience

교육 기관: Kenneth N

•

2022년 8월 18일

excellent presentation

교육 기관: SONALI H

•

2021년 10월 30일

better experience

교육 기관: Carlos A R Z

•

2020년 6월 19일

Great course :3

교육 기관: shakti k

•

2022년 9월 18일

excellent

교육 기관: Pris A

•

2021년 2월 18일

Perfect!

교육 기관: ABDUL H H

•

2021년 4월 4일

good

교육 기관: Himanshu S

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2021년 6월 14일

Information given is not complete

교육 기관: Maximilian B

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2020년 7월 3일

I am not very happy with this course. The instructor just rushes through some inside his formerly prepared jupyter notebook and his explanations on the actual code snippets are very short and not very understandable. Also he needs to work on his presentation skills as he struggles a lot during with finding the right words for his explanations during the course. This could have been prepared a lot better.

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