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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

4.6
332 个评分
99 条评论

课程概述

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....

热门审阅

DT

Mar 18, 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.

OS

Aug 30, 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.

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26 - AWS Computer Vision: Getting Started with GluonCV 的 50 个评论(共 99 个)

创建者 Ansari A M

Jul 09, 2020

The course was very helpful, all thanks to team coursera !!!!

创建者 Karm P P

Jul 26, 2020

its very good to learn step by step....thanks a lot coursera

创建者 Santosh S S

May 02, 2020

Great Experience!!!

Best Course Instructors,Excellent Course

创建者 Aditya h

May 14, 2020

enjoyed the course. great way to learn how to use GluonCV

创建者 Soumya P

Sep 17, 2020

Its a great experience for me to work with mxnet

创建者 Chiang B H

Jul 02, 2020

Well explained course. Great programming test!

创建者 Vishal V G

Jul 13, 2020

It was a very useful and needful session.

创建者 BHAVESH S

Jun 25, 2020

I am learn AWS COMPUTER VISION very easy

创建者 Manish P

May 11, 2020

Learnt a lot... Thank You Coursera & AWS

创建者 Edgar I

Apr 15, 2020

Excelente curso, muy recomendable!

创建者 Clinton E

Aug 11, 2020

I am very satisfied! nice course!

创建者 DEVENDRA V

Jul 30, 2020

best course ever on this platform

创建者 Mohit N

Jul 16, 2020

Best course on computer vision

创建者 Aman h

Jun 09, 2020

Valuable knowledge I received

创建者 Madhumitha S M

Jul 20, 2020

This course is upto stack

创建者 Gokulakannan S

Apr 23, 2020

The course was top notch

创建者 Sumeet Y

Jul 15, 2020

Amazing experience!!

创建者 Muhammad S A

Jun 03, 2020

Excellent Course.

创建者 Maksim K

May 10, 2020

nice starter pack

创建者 PRASHANT K G

Jun 13, 2020

excellent course

创建者 Shashikant K

Jun 16, 2020

Fantastic class

创建者 MD A R A

Jun 26, 2020

Excellent!!!

创建者 Abhas K S

Jun 09, 2020

Great Course

创建者 Prasanga N D

Jul 28, 2020

good course

创建者 Aninkan G

Jun 23, 2020

Nice course