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学生对 亚马逊网络服务系统 提供的 AWS Computer Vision: Getting Started with GluonCV 的评价和反馈

359 个评分
102 条评论


This course provides an overview of Computer Vision (CV), Machine Learning (ML) with Amazon Web Services (AWS), and how to build and train a CV model using the Apache MXNet and GluonCV toolkit. The course discusses artificial neural networks and other deep learning concepts, then walks through how to combine neural network building blocks into complete computer vision models and train them efficiently. This course covers AWS services and frameworks including Amazon Rekognition, Amazon SageMaker, Amazon SageMaker GroundTruth, and Amazon SageMaker Neo, AWS Deep Learning AMIs via Amazon EC2, AWS Deep Learning Containers, and Apache MXNet on AWS. The course is comprised of video lectures, hands-on exercise guides, demonstrations, and quizzes. Each week will focus on different aspects of computer vision with GluonCV. In week one, we will present some basic concepts in computer vision, discuss what tasks can be solved with GluonCV and go over the benefits of Apache MXNet. In the second week, we will focus on the AWS services most appropriate to your task. We will use services such as Amazon Rekognition and Amazon SageMaker. We’ll review the differences between AWS Deep Learning AMIs and Deep Learning containers. Finally, there are demonstrations on how to set up each of the services covered in this module. Week three will focus on setting up GluonCV and MXNet. We will look at using pre-trained models for classification, detection and segmentation. During week four and five, we will go over the fundamentals of Gluon, the easy-to-use high-level API for MXNet: understanding when to use different Gluon blocks, how to combine those blocks into complete models, constructing datasets, and writing a complete training loop. In the final week, there will be a final project where you will apply everything you’ve learned in the course so far: select the appropriate pre-trained GluonCV model, apply that model to your dataset and visualize the output of your GluonCV model....


Mar 17, 2020

I really liked this class. The labs were fun to do. I am hoping to pass the AWS Machine Learning certification and I am hoping this class got me closer to that goal.

Aug 29, 2020

This course is great and very helpful. It is highly recommended for anyone who wants to start using AWS especially for computer vision projects.


76 - AWS Computer Vision: Getting Started with GluonCV 的 100 个评论(共 102 个)


Jun 10, 2020


创建者 Rajeev y

Jun 9, 2020


创建者 Chathura S R

Jun 9, 2020


创建者 Aymen R

Jun 25, 2020



May 19, 2020

This course is very good with its contents of the beginners in Computer Vision. The course covers the End--to-End process for the computer vision tasks along with the related theoretical concepts.

The course also includes some of the practice assignments which are graded to test the knowledge and understanding of the students.

Looking after for other such courses related to other advance concepts of computer vision and machine learning.

创建者 kieran c

Nov 15, 2020

you really need a theoretical background in AI before you start. The labs were ok, but it would have been an awful lot better if a preconfigured VM was exposed on AWS or a proper image was made available for docker.

The course was a bit confused i.e. the AWS soft sell, then rapid change to advanced theory and code, but I have to say it was very good.

创建者 Kuldeep S

May 21, 2020

The course is structured very well, being a first time learner having some knowledge of neural network and jupyter notebook, it was easy to understand. During the course it was hard to create assignment questions but they were really needed to clear concept. Overall It is good course.

创建者 Michael L

Jun 16, 2020

Very well developed course. It's both an introduction to AWS for machine learning and hands-on labs on GluonCV. Would like to see a new course with more advanced topics!

创建者 M. H A P

Aug 21, 2020

Graded Assignment is too hard, not recommended for beginner

创建者 Rachit S

May 20, 2020

some topics could have been explained more in detail

创建者 Dr. V A D

May 28, 2020

Very informative course. I learned a lot ...

创建者 Abrar

May 25, 2020

not beginner-level course

创建者 Umesh k s

Jun 30, 2020

Best cource for student

创建者 Bhargav M

Jun 12, 2020

Good for knowledge

创建者 Ashish K

Jun 11, 2020

great learning

创建者 Ravi R S

Jul 26, 2020

great course


Jun 10, 2020

help thanks

创建者 Hemanth K y

Jul 7, 2020


创建者 Vanshika S

Jun 27, 2020

This is a beginner course but is does not seems like that.

Some more details and explanations of the programming part would really help to the students like me who don't have any past experience with machine learning.

创建者 Sandeep S

Jul 19, 2020


创建者 Kristoffer H

May 21, 2020

If you want a course with a lot of holes between what is covered and what your expected to do then this is the course for you. If you ask for help about stuff not covered in the course it can take a week or more(some people go 15+ days without a response) to get something about it being against the honor code to help. Well its apparently against the honor code to teach too.

创建者 Nikhil Y

May 18, 2020

Not so good course.AWS apply charges on many things.I was worried at every step .And alsos the instructor don't tell clearly how to install dependencies and how to perform task.

创建者 Bharath A

Sep 19, 2020


创建者 oleg r

Feb 20, 2020

It seems this company is not honest. They set deadline but don't react on request about problem in company side. It makes me nervous.

When I run script of Lesson 3 Practice Assignment in my AWS no one error occured

but when I uploaded script here it could not download dataset:

Downloading /home/jovyan/.mxnet/datasets/cifar10/cifar-10-binary.tar.gz from

download failed due to ConnectionError(MaxRetryError("HTTPSConnectionPool(host='', port=443): Max retries exceeded with url: /gluon/dataset/cifar10/cifar-10-binary.tar.gz (Caused by NewConnectionError('<urllib3.connection.VerifiedHTTPSConnection object at 0x7fa78f41c400>: Failed to establish a new connection: [Errno 110] Connection timed out'))")), retrying, 4 attempts left


Jun 11, 2020

Great learning or platform