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Отзывы учащихся о курсе Convolutional Neural Networks от партнера deeplearning.ai

4.9
звезд
Оценки: 40,149
Рецензии: 5,315

О курсе

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....

Лучшие рецензии

RS
11 дек. 2019 г.

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.

AG
12 янв. 2019 г.

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.

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4976–5000 из 5,288 отзывов о курсе Convolutional Neural Networks

автор: Klas K

1 дек. 2017 г.

The subject of this course is very interesting and I love that it is so bleeding edge. But the quality needs to be improved. Many videos repeat the same sentence again and again and seem to be very poorly edited. But even more annoying (and time consuming!) are errors and inconsistencies in the excercises. Most Notably in the grader (triplet_loss for week 4). Also, the changes to the quiz result displays are not helpfull: I was told that my answer was wrong for at least 2 questions where I was pretty sure and I would have liked to see that the answer I intended to give really is the wrong one. Maybe I just clicked the wrong checkbox unintentionally.

автор: Raj S

26 янв. 2018 г.

Course material is good but lacks in the area on how to use tensorflow. Unfortunately, tensorflow documentation itself is terrible. Testing and grading systems are buggy and haven't been fixed for months (check the forums). Specifically, for the first programming assignment when one of assignment functions returns correct answer based the specifications provided in the code the grader grades it 0 and grades it correct when you violate the specifications and generate a wrong answer. In the quiz, portions of the questions are blank/missing and one has to totally guess the answer (obviously I was unlucky to guess both my questions wrong :( )

автор: Guenther M

30 июля 2020 г.

Had problems with assignments in Week4 : the strange thing: sometimes everything is explained in maybe even to much detail, then again there are cases where one feels fooled like when you have to use np.sum() instead of tf.reduce_sum() in the verify()-cell. By suggesting the use of tf.reduce_sum in the cell before you indirectly suggest its usage also later on! And this really doesn't add anything to your qualification, it is just annoying having to skim a lot of threads in the forum to finally find out the solution.

And more care should have been given to the videos: Andrew's repetitions of whole sentences should have been cut out!

автор: Nathan Y

4 дек. 2017 г.

While as always Professor Ng was brilliant and informative, the final homework assignment (face recognition) was a disaster. Not only could we not load the weights because of corrupt files, but when that was resolved and the homework was submitted, the grader would only pass students who intentionally answered the Triplet section of the code wrong. What made this especially painful was the time it took to run the models. Tensorflow is not the easiest code to debug. One of the mentors from the course needs to monitor the forums closely - twice a day would not be too often. React and take charge when things start going badly.

автор: Abhishek R

22 сент. 2019 г.

The course material is really good and Andrew explains things really well. However, the programming assignments cause a lot of problem owing to the performance of the grader where by correct answers are marked as incorrect/incomplete and the only option to submit the assignment OR get it graded correctly is to follow steps from the forums to make changes to the files to trick the grader in order to get it submitted. From the forums it seems like these problems have been there for over 2 years and still has not been fixed. Overall the programming assignments are really good and helps in understanding the implementations.

автор: Adi G

5 нояб. 2019 г.

I was taking this course because I hope to apply machine learning to biological problems. So while the first two weeks were great and super general, the third and particularly the fourth weeks were less relevant to me at this point but I had to struggle with them to get the certificate. Ideally, I would say that a way to improve this would be to create another week, dedicated either to biological problems or to something more general to all and let the students choose between the content of that week vs. the current 4th week. Another option is to make this a 3-week course and leave the 4th week entirely optional.

автор: Vincent S

12 янв. 2020 г.

The video lessons gives very clear and understandable concepts but I didn't feel that the coding exercises will help me to write my owns. I could easy fill in the blanks and get the required grades but I have to admit that for the most of it I didn't understand what I was doing or what was happening in the part I didn't have to fill in. I have a reasonably strong mathematical background and barely no coding knowledge (a bit of Matlab and beginner python training). The whole deeplearning program was going relatively well up to the coding exercises in this course which jump a step too much for me.

автор: David

19 авг. 2018 г.

Not as great as the previous three courses. The exercises here are much more challenging than before, but not always for the right reasons. A thorough primer on Tensorflow should be made mandatory in this course. A lot of the time you eventually manage to complete the exercises without really knowing what you are doing. The subject matter in this course is also more complex than in previous courses, so more attention needs to be put on really making students understand the fundamentals thorougly. Also, sometimes buggy or inexplicable grader output. Andrew Ng is still a great instructor though.

автор: Mike L

17 нояб. 2017 г.

I have been a big fan of the series. I think it is a must-take series. I took this course when it was freshly released. The materials and programming assignments were quite good from week 1 to 3. However, the week 4 programming assignment was not ready. I encountered a few issues in the autograder and test data loading. I burned some time tracking down them. Fortunately my fellow classmates were very helpful in the forum. I am sure all problems would be solved in coming weeks. Just keep a mental notes.

Having said that, the materials is worth the pain. Go take it!

автор: Jonathan S Y P

15 дек. 2019 г.

La verdad este curso no me gustó mucho porque fue demasiado teórico y habían partes que uno se perdía de tantas formulas... por ejemplo en la tercera semana había una parte de la formula que decía 3x3x8 y como a los 6 vídeos siguientes, explicaron a que correspondía el valor de 8 (Si se hubiera explicado eso desde el primer vídeo hubiera sido más claro todo desde el principio). Este tipo de temas me parece que es más interesante verlo como un tutorial; donde a medida que se va explicando teoría, se va mostrando como hacerlo en x lenguaje, ya sea, python, c# u otro.

автор: Foad O

2 нояб. 2021 г.

T​he course is pretty good overall. However, the programming assignments need much improvement. I realize that teaching Python syntax and programming is not really part of this course, but if students are expected to do coding, there needs to be some more detailed lessons/sections to cover the basics. While providing vague, inconsistent and riddle-like "hints" in the middle of the programming exercises make for some interesting brain exercises, they are certainly not helpful at teaching the students what they need to know in order to write correct code.

автор: Rahul G

18 авг. 2021 г.

Wonderful course by Dr. Andrew Ng but it would be even better if the course offered EXECUTION EXERCISES following Google AI courses (see below)

https://developers.google.com/machine-learning/crash-course/introduction-to-neural-networks/playground-exercises)

Since many of us want to learn the course material and EXECUTE COMMERCIAL (or SEMI COMMERCIAL CUSTOMIZED) CODES and NOT INTERESTED in PROGRAMMING/CODING please provide GUI driven online execution modules INSTEAD OF PROGRAMMING EXERCISES !

Thanks,

Rahul Gupta rahulgupta2020@gmail.com

автор: Amod J

18 мар. 2018 г.

Really liked the course content but the true learning was in the homeworks that had the implementation details. After completing the course I was unable to download my own completed assignments as the course assignments were locked out for me. I don't want to re-submit any of them but I want to download my work to be able to refer to it and learn from it. I can see posts in the forum asking me to download them when the next session of the course becomes available, but I cannot afford to keep on paying ~ $50 subscription until it does.

автор: Mark P

9 дек. 2017 г.

The content covered is excellent as with the other courses.

However the material in this videos etc have many editing glitches. In addition some of the notebook based programming assignments are misleading and have minor errors that caused auto-grader issues.

In addition the programming assignments seem to be dumbing down. You spend lots of timing solving syntactic nuances of tensorflow, Keras etc rather than being asked to solve cerebral problems that help understanding of the concepts.

автор: Grant G

28 янв. 2018 г.

This covers hugely important information and really deserves five stars, but it is fundamentally clumsy. Even leaving aside the unprofessional disaster that is the week 4 assignment 2 grader, the difficulty level is all over the place and the description of the style transfer is borderline incomprehensible (possibly because Prof. Ng is trying to soft-pedal the linear algebra?)

Coursera, Prof. Ng, please take a second look at this one. It needs -- and deserves! -- better work.

автор: Jalaz K

23 нояб. 2018 г.

Assignments really need to be improved. Of all the courses in this specialization, this particular course frustrated me a bit. Thanks to the discussion groups, I was able to sail through.

Moreover, Grader should provide the summary of error in our submission rather than just showing wrong submission. Course Material was really good. 5 on 5 for that part, but the assignments really troubled me and others as well, as can be easily seen in the discussion groups.

автор: Andreas B O

17 янв. 2020 г.

Lectures were great. The descriptions for all applied operations, algorithms, etc. by Andrew are excellent. However, the Programming Assignments this time around demanded a lot of looking up TensorFlow and Keras functions (even during the Keras Tutorial). Especially Week 3 was a struggle for me. At some point, the framework simplicity is turned into rather harsh complexity. A better explanation of what TensorFlow/Keras commands to would be of advantage.

автор: Asif I

23 дек. 2017 г.

First of all, thank you for providing such a rich content.

I know its hard to strike a balance between covering content and "actually" delivering them to the student. Course #3 and especially #4 felt very rushed when it came to the exercises. The tensorflow concepts that came back out of nowhere and solutions would have been nearly impossible without the copious hints.

PS: Course 4 "happy house" face recognition assignment was choke full of bugs.

автор: Nitin S

1 июля 2020 г.

Very good introduction to concepts on Convolution Networks. It would have been great to put more emphasis on how actual models like "FRmodel" are trained vs tested. E.g it would be great to provide information on the fact that 3 parallel networks need to be used that share weights. So more exposure to practical aspects of implementation would be useful. Essentially a lot more time can be spent on exercises than what is meant for them

автор: Vahid J

7 нояб. 2020 г.

Unlike other courses in this specialty, this course was primarily focused on describing some specific methods/approaches (which happened to be very popular) rather than describing high-level concepts. At some points, I had a feeling that the course material reads more like a journal club. While journal clubs can be very useful, I preferred more if this course was mostly focused on overall/generic concepts.

автор: Michele T

5 апр. 2020 г.

This was an interesting course. It provides a high level look at face recognition/verification and various state-of-the-art aspects of convolutional neural networks. The one thing I found frustrating in this course was the grader. It was very particular for at least one homework assignment on the order in which you entered your variables. I spent way too much time on debugging for simple things like that.

автор: Matthew C

19 июня 2018 г.

The content was great, and is probably the best available. However, the grader was so flaky it really shook my confidence in the material. I'm the type of person who will try and try until I'm literally about to give up before I look for help in the forums, so I lost a LOT of time on these exercises. This was by far the WORST of the five courses in the specialization. Sorry to yell, but YOU CAN DO BETTER!

автор: Samuel R

23 окт. 2020 г.

The Keras and TensorFlow versions used in this course are by now to a large degree outdated. The Newest TF version is at the date of writing 2.3, while the course uses <2.0, so many of the functions used are deprecated in the newer versions

However, Andrew's explanations are great as always except for the convolutional implementation of sliding windows in the 3rd Week. (therefore only 3 stars this time)

автор: Alan S

19 нояб. 2017 г.

Depplearning.AI: Please do not release content unless it is ready. The content is fine, but the assignments were clearly hastily put together and had basic bugs discussed all over in the forums. In particular, week 4 is a complete mess. Boiler-plate code that doesn't even relate student-content (to load a dataset) doesn't even run for many people. This wastes everyone's time. Really disappointing.

автор: Bjorn E

19 нояб. 2019 г.

Overall a great intro to CNNs. But the last part of the course on object detection and facial recognition is very superficial. It explains the logistics of the disciplines (how to keep track of bounding boxes, etc), but it doesn't teach how to actually build such a system. The exercises make you fill in a bunch of indices and do vector math, but deliver the actual hard parts inside black boxes.