Chevron Left
Diabetic Retinopathy Detection with Artificial Intelligence に戻る

Coursera Project Network による Diabetic Retinopathy Detection with Artificial Intelligence の受講者のレビューおよびフィードバック

4.6
29件の評価
8件のレビュー

コースについて

In this project, we will train deep neural network model based on Convolutional Neural Networks (CNNs) and Residual Blocks to detect the type of Diabetic Retinopathy from images. Diabetic Retinopathy is the leading cause of blindness in the working-age population of the developed world and estimated to affect over 347 million people worldwide. Diabetic Retinopathy is disease that results from complication of type 1 & 2 diabetes and can develop if blood sugar levels are left uncontrolled for a prolonged period of time. With the power of Artificial Intelligence and Deep Learning, doctors will be able to detect blindness before it occurs....

人気のレビュー

AB

2021年9月12日

The course is very nicely explained. I would recommend this project for those who have some prior experience in Python and CNN to try out this exciting real world project.

GK

2021年3月25日

Well Instructed Project. Step by step explanation and analysis of every problem is simply excellent. Highly recommended project.

フィルター:

Diabetic Retinopathy Detection with Artificial Intelligence: 1 - 9 / 9 レビュー

by Pavan k

2021年3月26日

Well Instructed Project. Step by step explanation and analysis of every problem is simply excellent. Highly recommended project.

by ESTIBALIZ D

2021年4月8日

very practical also informative.

by Pranjali A

2020年12月21日

Instructor could've talked more in depth about the neural networks and how it works. Some parts of the theory and intuition video were confusing.

by Hualai T

2021年3月29日

Too short, wish that this project can expand into more details.

by Megan D

2021年12月21日

This is my first guided project course I took on Coursera, and it is simply amazing!! Even though I took a couple of AI courses from Coursera, which concentrate on the theoretical details , my confidence in applying those knowledge after taking this practical course. BIG THUMB UP for the instructor , who explain the whole concept including almost every line of code with the required details for one to digest the topics easily.

by Asutosh B

2021年9月13日

T​he course is very nicely explained. I would recommend this project for those who have some prior experience in Python and CNN to try out this exciting real world project.

by Reem A

2021年7月13日

thank you

by Edward N

2021年9月9日

a1

by Paul M

2022年3月14日

It is unclear to me who could tangibly benefit from this course. Wrong terms are being used, while the course claims to provide a high-level overview over the concrete modeling approach, little to none is given for students new to the field to grasp what is happening while even over the very short runtime time is wasted on entirely irrelevant matters (e.g. google what performance resnets achieve on imagenet).