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Convolutional Neural Networks(으)로 돌아가기

deeplearning.ai의 Convolutional Neural Networks 학습자 리뷰 및 피드백

4.9
별점
39,693개의 평가
5,251개의 리뷰

강좌 소개

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....

최상위 리뷰

AG
2019년 1월 12일

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.

OA
2020년 9월 3일

Great course. Easy to understand and with very synthetized information on the most relevant topics, even though some videos repeat information due to wrong edition, everything is still understandable.

필터링 기준:

Convolutional Neural Networks의 5,222개 리뷰 중 5101~5125

교육 기관: Chengqian W

2018년 7월 31일

Some technical issues/errors in lectures.

교육 기관: Patrick M

2019년 2월 8일

Too many mistakes in assignment material

교육 기관: Karan D

2018년 1월 7일

there were bugs in the jupyter notebooks

교육 기관: Mohammad A

2020년 9월 19일

programming assignments are not helpful

교육 기관: eric v

2018년 4월 19일

some of the quizzes were a little buggy

교육 기관: Walid M A

2017년 11월 17일

I did not like the assignments of w#4

교육 기관: Pakhapoom S

2021년 3월 14일

The videos need to be edited properly.

교육 기관: sai d s

2019년 1월 17일

Little bit hard programming Excercise

교육 기관: Xirui Z

2021년 4월 7일

Too hard for someone new to tf.

교육 기관: Sanskar j

2020년 6월 18일

Assignments can be made better

교육 기관: Jisheng L

2018년 6월 15일

Need improvement on assignment

교육 기관: Pedro C

2018년 6월 10일

notebook were not functional

교육 기관: Modassir A

2020년 5월 11일

need improvement of content

교육 기관: Olatunji O

2019년 2월 12일

Notebooks are a bit buggy

교육 기관: Yi-Hao K

2018년 1월 20일

Serious bug in assignment

교육 기관: Yide Z

2018년 1월 13일

too many errors in test

교육 기관: akshat

2021년 6월 25일

Labs should be tougher

교육 기관: KevinZhou

2018년 5월 8일

部分内容讲的不是很清楚,有些剪切不好,有重复

교육 기관: Kenneth C V

2020년 12월 4일

Very complex Subject

교육 기관: zz

2018년 3월 5일

没有翻译 tenserflow也讲得不好

교육 기관: Pavao S

2018년 3월 2일

Not enough theory

교육 기관: neda m

2020년 6월 22일

too theoretical

교육 기관: Volker H

2017년 12월 16일

too many bugs

교육 기관: Shimaa

2021년 8월 30일

so hard :(

교육 기관: Logos

2020년 8월 27일

It was okay. Andrew is obviously very knowledgeable, and there is a wealth of knowledge here. I could go through it a couple more times and still pick up new stuff.

That being said, I've heard him mention he did these videos at like 1 or 2 in the morning after work, and it's very obvious from the videos. He makes so many mistakes that every other lecture (it seems like) has a **CORRECTION** notification next to it. I mean it's great they give this additional correction information, but it would be even better if you just redid the video.

Furthermore, he like stops in the middle of the videos and then repeats the last sentence he said, because he made another mistake. I get it, Andrew is very successful, he's very busy, and I am definitely grateful for the knowledge he's provided in this course. But this makes for a very poor learning experience, because I'm taking notes, and I have to go back and redo them, plus the general angst you get when you're learning something and someone's like "oh wait nope that's not right, forget that." Well for God's sake I already learned it.

Finally, the submission assignments are the most annoying things I have ever come across. They are riddled with errors and misguided information where they literally tell you to use the wrong parameters, and then they never fix it. You have to go into the discussions to find out why your code is wrong, even though you're doing it right.

Then, you'll get everything right on your code for the test cases, and when you go to submit it fails you. And when I say it fails you, it gives you a literally 0 out of like 30 points. And the grader output just says "your submission was incorrect" like no way, I had no idea. Thank you for that very **cough** helpful piece of info.

If you go to the discussions, you find out this is actually a problem with how the grader is built, because if you don't format your code exactly the right way, it fails you, even if your solution is correct. I don't understand why it can be right when you run test cases, but submitting it fails.

Overall, I give it 3 stars before the poor grading, but because of the poor grading performance I have to bring it down to 2. I can't tell you how much time I wasted trying to figure out why my code was wrong just to realize it was right, but they screwed up their implementation.

In conclusion, this reminded me of a college course, where the professor has a ton of knowledge and is in high demand, and doesn't really care whether you get anything out of the course or not. It's sloppy, doesn't seem to be maintained very well, and most of the mentor's responses are literally "did you look at your colleagues similar questions?" Like no I didn't, that's why I'm asking. Why am I paying you so I can spend more time debugging your screw ups? Or maybe I did and I still don't get it because your explanations are ridiculously unclear.

I have one more course in this specialization and I absolutely can't wait for it to get over with so i can move on to more productive (and immersive, since these exercises are just one off "do this then do that" instructions, I still don't know how to set up a Deep Learning project from scratch) ways to learn Deep Learning. If Andrew wasn't so knowledgeable about this topic, I wouldn't even take it because it's that bad. But really you can't get this type of knowledge in such a condensed form anywhere else.