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学生对 提供的 Convolutional Neural Networks 的评价和反馈

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This course will teach you how to build convolutional neural networks and apply it to image data. Thanks to deep learning, computer vision is working far better than just two years ago, and this is enabling numerous exciting applications ranging from safe autonomous driving, to accurate face recognition, to automatic reading of radiology images. You will: - Understand how to build a convolutional neural network, including recent variations such as residual networks. - Know how to apply convolutional networks to visual detection and recognition tasks. - Know to use neural style transfer to generate art. - Be able to apply these algorithms to a variety of image, video, and other 2D or 3D data. This is the fourth course of the Deep Learning Specialization....



Sep 02, 2019

This is very intensive and wonderful course on CNN. No other course in the MOOC world can be compared to this course's capability of simplifying complex concepts and visualizing them to get intuition.


Jan 13, 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.


1 - Convolutional Neural Networks 的 25 个评论(共 2,963 个)

创建者 Gyuho S

Apr 25, 2019

This course is definitely tougher than the first three courses. Challenging but worth it.

创建者 Farzeen H

Jan 12, 2019

Amazing! Feels like AI is getting tamed in my hands. Course lectures , assignments are excellent. To those who are not well versed with python - numpy and tensorflow , it would be better to brush up.

创建者 David B C S

Dec 17, 2018

Great course, easy to understand and very useful. The explanations are very clear, as is expected from the professor. The purpose of the course is for you to have a practical comprehension of CNNs, it will give you the necessary tools to implement you own networks, but it will not get into the specifics of each model. Nevertheless, all of the resources are referenced, which makes it very easy for you to dig deeper on any specific topic covered on the course.

创建者 Aleksa G

Jan 13, 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.

创建者 fabrizio f

Dec 17, 2018

Very good however most of the effort is applied in learning and applying programming (tf, Keras) than actually thinking about the DL models and practicing different scenarios.

创建者 Ed B

Nov 03, 2017

Wonderful course. Covers a wide array of immediately appealing subjects: from object detection to face recognition to neural style transfer, intuitively motivate relevant models like YOLO and ResNet.

创建者 Joshua M

Jul 31, 2019

Content is great, but videos could be trimmed to cut retakes. A big issue is that guidance for programming assignments abruptly drops off from extreme hand-holding to being thrown in the deep end.

创建者 Markus B

Dec 05, 2018

Great course. The only improvement I'd wish is to get a better introduction to the concepts of Tensorflow and Keras.

创建者 Sergei S

Apr 29, 2019

Some parts of the course seemed incomplete to me, wanted more information on why things work exactly as described. Last week assignments have a number of uncertainties/bugs.

创建者 Xinwei B

Feb 13, 2019

When I am doing the programming assignments, I felt that some part were quite difficult since I had no background in neither Keras nor Tensorflow. It was helpful that in one of the previous courses there was a tutorial for the basics of Tensorflow. But for Keras I felt that there is a gap between what I have and what is needed for the assignment. So I would suggest a more thorough tutorial for Keras. Maybe several short tutorials talking about the implementations and ideas of Tensorflow & Keras may help a lot.

创建者 Michael J

Jan 02, 2019

A short (but cogent) overview of CNNs with a ton of references to read through and much more interesting assignments (than previous courses). I really enjoyed this course, I got a ton of exposure from it.

创建者 Devjyoti M

Apr 22, 2019

This is one of the best courses for CNNs. This gives a very deep understanding of the concepts and helps to understand the brains behind the CNNs and their working in application based environments.

创建者 Daniel G

Feb 14, 2018

Too much hand-holding during assignments, although still very good directions. Obviously the issue with the final programming assignment needs to be addressed. Fantastic lecture material, as always.

创建者 Tian Q

Jan 01, 2019

Excellent introductory course for CNN. The basic ideas and key components are explained clearly. Coding assingments helped me understand the algorithm to every little detail.

创建者 Cosmin D

Jan 04, 2019

Good content, videos have the occasional editing hiccups that also affect other courses in this specialisation. Assignments could be a little bit harder but do a reasonable job at familiarising with useful deep learning frameworks.

创建者 Ralph J R F

Apr 27, 2019

I think it's a good idea to remove repeated parts in the videos. Also, put all pieces toguether to give a better overview of the object detection solution

创建者 Huijun P

Apr 18, 2019

Great lectures but the programming assignments feel as if it is testing your proficiency with tensorflow which is neither formally covered in the lecture nor the most intuitive framework to understand so you'll spend so much time digging through convoluted tensorflow documents and qna and whatnot to debug your codes that you would rather learn tensorflow formally first and then take this course and still end up finishing it faster than only going through this course only but it is only the programming assignments that basically assume that you are already familiar with the tensorflow framework so if you are only going to go over the video lectures it gives a great overview of how CNN works and many useful algorithms which can applied to a assortment of situations

创建者 Stefan J

Dec 30, 2018

Theoretical material was great as always. However, programming assignments were poorly commented in some cases which results in unnecessary confusion.

创建者 Sriram G

Feb 10, 2019

Homeworks are too canned and do not promote deeper understanding.

创建者 Alberto B

Feb 08, 2019

Assignments are very bad explained

创建者 divya p p

Feb 18, 2019

Dear Instructors,

This is most frustrating course in all of your courses so far. The instructions were completely misguiding the candidates from YOLO implementation onwards. All along you presented the course very well. But when come to most important topics, we had to focus on syntactical errors. But we are supposed to spend time on understanding the algorithms at this level. Dont know why this 180 degrees turn taken by you. If you intentionally designed this course then fine. Otherwise, you should seriously think about rework on the instructions. Few links to hints were taking to some pages in github with just folders.

I am sure , many learners here have such same opinion. I can see this in the forum postings.

From YOLO onwards, you were not giving the big picture of the task. This is confusing. We are lost, where we are heading by the mid of the assignment.

With all due respect to your highly precious time, I request you to enhance the assignment instructions.

All motivation I got from previous course, losing because of this course.

Personally, I feel YOLO easy to understand, but instructions were misguiding and confusing the candidates.

This is my honest feedback, as I very much like this course. I am going forward for the 5th course in this series.

Last but not least. Thank you for making this high quality knowledge made available for public with easy access via Coursera.

创建者 Basile B

Apr 30, 2018

IoU validation problem is known but nothing as been done to resolv it

video editing problem

unreadable formula in python notebook for art generation (exemple :

$$J_{style}^{[l]}(S,G) = \frac{1}{4 \times {n_C}^2 \times (n_H \times n_W)^2} \sum _{i=1}^{n_C}\sum_{j=1}^{n_C}(G^{(S)}_{ij} - G^{(G)}_{ij})^2\tag{2} $$

What append ? that was great so far... =(

创建者 白思开

Jan 28, 2019


创建者 Nyamerdene O

Jan 28, 2019

It is a very excellent course. It including from CNN's foundation to the latest Deep CNN architecture.

创建者 Martin Z

Jan 27, 2019

Thanks a lot for this great course :-) Learned a hell lot!