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Вернуться к Image Classification with Amazon Sagemaker

Отзывы учащихся о курсе Image Classification with Amazon Sagemaker от партнера Coursera Project Network

4.6
звезд
Оценки: 94
•
Рецензии: 15

О курсе

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 image classifier 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 image classification algorithm from Sagemaker to create, train and deploy a model that will be able to classify 37 breeds 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 image classification, 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....

Лучшие рецензии

DZ

1 мая 2020 г.

This course is very helpful for you to create a warmup code with AWS Sagemaker and image classification.

SG

6 окт. 2020 г.

I love this course. Need to know more about custom mage codes in sagemaker.

Фильтр по:

1–15 из 15 отзывов о курсе Image Classification with Amazon Sagemaker

автор: Changwoo H

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17 апр. 2021 г.

This is Not 2hr course. It's takes 24hr or more. Instructor should have announced about train instances are not available in most of the cases. To extend limits students have to wait response of aws.

автор: DINESH A Z

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2 мая 2020 г.

This course is very helpful for you to create a warmup code with AWS Sagemaker and image classification.

автор: T S G

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7 окт. 2020 г.

I love this course. Need to know more about custom mage codes in sagemaker.

автор: Karem B

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11 сент. 2020 г.

very easy step by step guided project

автор: SUGUNA M

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19 нояб. 2020 г.

Good project based course

автор: XAVIER S M

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31 мая 2020 г.

Thank You !

автор: Doss D

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24 июня 2020 г.

Thank you

автор: purnachand k

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12 мая 2020 г.

Excellent

автор: Md. T U B

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2 сент. 2020 г.

great

автор: p s

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22 июня 2020 г.

Nice

автор: Florian C

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18 апр. 2021 г.

You get the basics explained quick and dirty but there will be still much you do not understand and have to learn about after this project both regarding SageMaker and its libraries as well as building and deploying ML models in general .

автор: Matapathi S

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15 июня 2020 г.

Thank you

автор: SAI P M

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29 июня 2020 г.

not bad

автор: Wen-Wei X

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5 апр. 2021 г.

too simple, did not show the overall accuracy in validation test set and potential way to improve it

автор: Tobias H

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25 июля 2020 г.

i want to the loading data and more

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