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Learner Reviews & Feedback for Convolutional Neural Networks by DeepLearning.AI

4.9
stars
39,878 ratings
5,273 reviews

About the Course

In the fourth course of the Deep Learning Specialization, you will understand how computer vision has evolved and become familiar with its exciting applications such as autonomous driving, face recognition, reading radiology images, and more. By the end, you will be able to build a convolutional neural network, including recent variations such as residual networks; apply convolutional networks to visual detection and recognition tasks; and use neural style transfer to generate art and apply these algorithms to a variety of image, video, and other 2D or 3D data. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI....

Top reviews

AG
Jan 12, 2019

Great course for kickoff into the world of CNN's. Gives a nice overview of existing architectures and certain applications of CNN's as well as giving some solid background in how they work internally.

RS
Dec 11, 2019

Great Course Overall\n\nOne thing is that some videos are not edited properly so Andrew repeats the same thing, again and again, other than that great and simple explanation of such complicated tasks.

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4901 - 4925 of 5,245 Reviews for Convolutional Neural Networks

By taowucheng

Jan 5, 2018

最后一个作业感觉有一些问题

By A 6 W A

Sep 22, 2020

great course

By Steve d l C

Aug 27, 2020

good course

By Sahil M

May 5, 2020

The Besttt.

By Ankur G

Sep 15, 2019

informative

By Sonia D

Jan 30, 2019

Very Useful

By Luca M B

Aug 1, 2018

Quite nice.

By Ayoub A I

Sep 2, 2021

Thank you!

By Rishi J

Jul 25, 2020

Insightful

By Yehang H

Jan 2, 2018

Some error

By Mohamed A M

Oct 5, 2020

thank you

By Yashwanth M

Jul 16, 2019

Very Good

By Dave

Jul 10, 2020

good job

By PRASANNA V R

Jun 30, 2020

Decent

By CK P D

Mar 31, 2020

Thanks

By Niranjan

Nov 25, 2017

Great

By Sumera H

Sep 13, 2020

good

By Isha J

Apr 5, 2020

good

By Subhash A

Mar 27, 2020

good

By VIGNESHKUMAR R

Oct 24, 2019

good

By Rahila T

Oct 8, 2018

Good

By Naveen K

Jul 17, 2018

good

By Panchal S V

Jun 28, 2018

Good

By CARLOS G G

Jul 24, 2018

g

By Volodymyr M

Apr 24, 2020

This is not an education in any way. Yes, Convolutional Neural Networks provides good overview of convolutional networks and technology behind it. I like the way Andrew Ng structured material and his way to explain some details. Unfortunately, as a common problem for all "Deep Learning Specialization", theoretical material only scratches the surface of the knowledge. There is nothing deep in terms of theory. You will have to spend quite a lot of time digging for information yourself if you plan to use course material for any practical task, or assignment. In order to get missing pieces, I got to go through whole Spring 2017 CS231n. It is fine if you have enough time to see two sets of videos, but I expected to get same quality of material here, on Coursera.

Another course issue is quizzes. I am puzzled what these quizzes are testing. Provided answers often assume tentatively more than one correct variant. Probability theory works against you - you may happen to select correct answers for some questions , but definitely, not all of them. In the same time, it is quite easy to derive correct variant from second try.

Course programming assignments are complete disaster. While I kind liked programming assignments from week 1 and 2, I felt like I wasted my time working on programming assignments from week 3 and 4. I expected programming assignment to guide me through some training of complex networks, give some practical insight, which I can use for real-life tasks, but it was not there.

There is a good introduction to TensorFlow, while Keras is not even touched. And many assignments of week 3 and 4 are using Keras. It is necessary to peek-up theory and practice regarding Keras elsewhere. After one get enough knowledge about Keras elsewhere - guess what - programming assignment becomes useless as education, because it is too trivial.

I really wanted to rate this course as Two-Stars, but video materials and programming assignments from week 1 and week 2 slightly improved my attitude.