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Volver a Deep Learning in Computer Vision

Opiniones y comentarios de aprendices correspondientes a Deep Learning in Computer Vision por parte de National Research University Higher School of Economics

119 calificaciones
31 revisiones

Acerca del Curso

Deep learning added a huge boost to the already rapidly developing field of computer vision. With deep learning, a lot of new applications of computer vision techniques have been introduced and are now becoming parts of our everyday lives. These include face recognition and indexing, photo stylization or machine vision in self-driving cars. The goal of this course is to introduce students to computer vision, starting from basics and then turning to more modern deep learning models. We will cover both image and video recognition, including image classification and annotation, object recognition and image search, various object detection techniques, motion estimation, object tracking in video, human action recognition, and finally image stylization, editing and new image generation. In course project, students will learn how to build face recognition and manipulation system to understand the internal mechanics of this technology, probably the most renown and oftenly demonstrated in movies and TV-shows example of computer vision and AI....

Principales revisiones


Jun 12, 2018

Excellent course! Quiz questions are conceptual and challenging and assignments are pretty rigorous and 100% practical application oriented.


Apr 19, 2019

Don't just read what's written on the projector. Try explaining it. And explain with code.

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1 - 25 de 31 revisiones para Deep Learning in Computer Vision

por Rohan K

Jul 24, 2018

Very poor instructions in course, can' even understand a thing.

1.Tutor does not explain clearly what exactly is happening, just reads the formula on screen as it is.

2.What is kernel and why we use it. Also what happens exactly when we convolutionalize,image matrix. Nothingggg is explained.

3. How one should solve the maths in graded assignments, when can't even understand the math behind the technique.

4. Speaking accent of tutor is very bad, can't understand if captions are not enabled.

I have taken many courses on coursera, which were very informative and in-depth explanation, but this course is just like National research university has nothing to do with if students are actually learning or not. It is more like earning money only.

There are several other cons which I have not mentioned.Very very disappointed.


Nov 06, 2018

Lecturer had a difficult accent to understand. Briefly put up formulas and graphs but didn't explain them. No examples were worked through yet the quiz required this to be done. To understand this subject I will have to go away and study this from another source before I can understand it.

por Kocić O

Sep 20, 2018


- excellent and challenging exercises

- relevant topics


- poor feedback and course management

- lectures that do not teach you anything, it is more a taxonomy of what exists out there than explanation of anything

por Jakub B

Nov 23, 2018


-thorough course material

-ambitious and interesting assignments


-there isn't ANY assistance from the instructors or the TA. If you check TAs then you'll see that all of them written 0 posts on the forum.

-most assignments are severely underspecified. This makes them much harder than they should be, and it makes students spend hours on minutiae of preprocessing instead of more important stuff.

por Nafiseh S N

Oct 30, 2018

Worst presentation ever! Hard to follow, he reads from a text with no explanation. The worst! I also have to read the transcript to understand what he is saying.

por Matt V

Sep 10, 2018

Some good topics and interesting homeworks, however, the lectures are rushed through without much explanation or examples, and there are many frustrating mistakes that belie the fact that this course is apparently not maintained and there is no support for students on the forums. Could be really good, but it's not there yet.

por 李朝辉

Dec 14, 2018

the descriptions of homeworks are sometimes ambiguous, students may spend too much time trying to understand. Also, I strongly recommend teachers can interactive with the PPT when lecturing, instead of reading the draft directly.

por Raymond P

Oct 02, 2018

Slides are not available, only the videos. Quiz questions are very unclear and ambiguous. Assignments have almost no direction and require many hours of commitment. Requires a significant amount of prior knowledge before taking this course. Would not recommend. Andrew Ng's specialization is much better.

por Потапчук А А

Aug 04, 2018

Lectures are good (mostly). But home assignments are very bad. Some links for datasets are broken. Admins did not fix it after a month (I found a message about it on the forum)!!! There are a lot of mistakes in a code. So, I spent a huge amount of time just for fixing bugs. It was very painful.

I think, administrators should read comments sometimes and update repos.

Some home assignments are very cool. But, mostly it is not possible to run it on a low-class laptop.

Moreover, there are a lot of mistakes in quizzes that was not fixed for a long time! So, people tried a grid search for answers. I definetely recommend to administration start fixing this bugs. This course is very good, but all this bugs discourage any desire to pass it.

por Alex

Jul 06, 2018

Course is very raw. Number of mistakes, missing lectures, missing subtitles, missing slides.Quality of lectures, especially in the starting weeks. From my point of view, teachers just read subtitles under the camera, making strange pauses, which ruins understanding.Overwhelming tasks (taking more than person's 20h each) with too few help.And no answers / support from the instructors during the course at all. Which is most disappointing, because other things can be fixed / tuned somehow.I will argue anybody from taking this course, until it's reworked and staff started to participate in the forums.

por Yury Z

Jun 20, 2018

Great content! Great assignments ideas. Problems with graders. Quizes and especially assignments, are loosely related to the lecture materials. The ability of authors to explain things is pretty week (it is not even close to Andrew Ng skills). The efforts necessary to complete assignments are ridiculously underestimated. You will need 10-20 hours or even more for each assignment, instead of 2hr specified. Total experience is very contradictory. I chose between 3 and 4. 3 is too low mark for these unique content, and creative assignment ideas, and I hope the assignment format could be improved in the feature, with not so many efforts (some tips, and intermediate assertions could help a lot). As for now, I could not recommend this course for wide audience, only for the most "desperate" students.

por Sahil J

Jun 12, 2018

Excellent course! Quiz questions are conceptual and challenging and assignments are pretty rigorous and 100% practical application oriented.


May 15, 2019


-> Instructors read scripts during the whole course

-> No lecture slide (seriously ? thanks a lot for the effort)

-> Lectures are instructive even if you already know a bit about computer vision

-> Some topics and technical points are unclear, and quickly done with


-> ALL assignments are peer graded, meaning you never know if you will get a grade before deadline

-> Forums and discussions are deserted, you won't find any help there

-> Instructors provide very little explanations and directions

-> Some assignments can be pretty tough to complete if you are not strongly familiar with CV

-> Some assignments are unrelated to lectures (Week1 Alignment, Week5 GAN)

Overall the course is really interesting and instructive, but it feels like it was designed in a rush.

You can look elsewhere for a good course about computer vision.

por 杨伟

Apr 29, 2019

I am not sure how to rate this course exactly.

1, It is difficult to study. mainly because it just list most tech in computer vision but without detailed is not better than reading the origin papers.

2, Some quizz are very confusing, Actually adding a little explanation will make the quizz more clear.

3, The assignments are not uniform. it did not give a uniform environments. you need setup the env by yourself.

4, But when you finished the course, you will learn a lot things.

por Rachepalli R R

Apr 19, 2019

Don't just read what's written on the projector. Try explaining it. And explain with code.

por Arnaud R

Apr 10, 2019

Some good and challenging assignements but overall the material is delivered poorly. Slides/Videos are rushed through, quizzes are messy and there is barely any help given. I was excited to do the course as a followup from but it ended being a chore. I still learned useful skills and concepts overall but be warned.

por Milos V

Feb 28, 2019

Computer vision is far the most difficult AI application, and for this the best course should be done to make ti clear. However, here we had awful lecturers (they are reading as robot!) and "hints" are often misleading or wrong... I gave 2 stars only because assignments were nicely connected, but that is all.

Message to the "AML-bosses": this course should not be in this specialization!!!

por Artem E

Jul 03, 2018

Very bad course in quality of performance. The authors created it, but did not support it. Multiple errors, lack of help on the forum and the absence of correction of obvious problems (link to download the GAN dataset)

por Erik G

Jun 07, 2019

Some lectures aren't clearly structured. The homework assignments have downstream dependencies (week 5 depends on earlier weeks) which is not the best format IMO.

por Gary

May 27, 2019

Not clear. And just focus on papers, not on basic structure or models.

por Suvankar P

May 21, 2019

No relation of videos and tasks

por Nabarun D

May 20, 2019

Worst course in the specialization.

por Jiachen L

May 05, 2019

Course homework is actually not well designed for Coursera platform, some homework is not quite relevant to Deep Learning (i.e., HW1 and HW2) and some is very hard to complete (i.e., the last one, I tried on CPU for about 2 weeks). Also, the slides are not shared for this course in the series.

por Anmol G

May 02, 2019

The content was good, but there are several drawbacks too

1 Content not explained well

2 Assignments had mistakes (like broken links, wrong descriptions)

3 Minimal or Non-Existing support from the staff.

por William

Apr 22, 2019

The task is really practical and useful, but the courses content is too general and I hope for the future it could include some papers reading assignment