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Вернуться к Convolutional Neural Networks

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

4.9
звезд
Оценки: 40,134
Рецензии: 5,314

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

OA
3 сент. 2020 г.

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.

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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5001–5025 из 5,286 отзывов о курсе Convolutional Neural Networks

автор: Santosh N

3 янв. 2018 г.

Course lectures and questions are very good. The programming assignments are also good questions wise, but the grading mechanism is quite annoying. We had to find out clumsy workarounds to get the correct grading, in one case, the code change needed for getting the correct grade did not result in the expected output. Coursera needs to change the method of grading programming assignments.

автор: Sinan S

22 дек. 2021 г.

In this course the material/resources regarding Keras is highly insufficient. So far I have made little progress in the programming assignments related to Keras and I achieved this by figuring out stuff by googling which took a long time. If the instructors could extend the course with stuff related to Keras it would be great. At least there should be references to sufficient resources.

автор: Jayson W

26 янв. 2019 г.

I can't believe the number of technical problems I've had with notebooks not saving my work on homework assignments. It's very frustrating. The content is good and I will continue with the course, but this is the first Coursera course I've had (actually, the whole series in this topic) where I have experienced the lost of work - I just lost about an hour on a homework assignment.

автор: David C S

16 июля 2020 г.

I am very annoyed with the evaluation of the notebooks. Not with the content itself, but with the support from instructors, which is non existent.

It took me two days and 10 re-submitions to solve a problem that was unrelated to the code, but to the behavior of the grader system. No one replied my cries for help in the discussions.

Very disappointed with the lack of support.

автор: Stephen W

7 дек. 2017 г.

The content of the course is very good, as with all the Andrew Ng / deeplearning.ai material. However production standards seem to have slipped for this one. Repeated sections in video material and a final notebook exercise that contained errors and required finding a work around that was posted in a discussion forum. I hope these things can be corrected for others.

автор: Murad O

17 нояб. 2017 г.

I have mixed feelings about this course in particular, although one learns many interesting and useful concepts, I did little implementation on my own. Also the involvement of Keras I found annoying, yes it eases the implementation of ConvNets, but while learning I would have preferred to use tensor flow instead, or even implement a simple NumPy ConvNet on my own.

автор: Francesco B

2 апр. 2020 г.

The content is very good. The exercises are a bit useless. Don' expect to be able to use tensorflow after this course. Furthermore, they teach the syntax of tensorflow 1 rather than the new 2. Therefore, when you try to solve the exercises you don't understand the discrepancies between the online documentations and what they want for these exercises

автор: Boyi Y

5 дек. 2018 г.

Excellent course! I have learned the skills to combine image processing with machine learning.

However, the assignment of the Week 3 has a problem that you have not fixed for a long time, and thus it wasted some time. And the assignment in Week 4 has problems of submitting, and that's why I only rated three stars. Hope you can fix the problems soon.

автор: mike b

4 февр. 2021 г.

First, there should be an upgrade to TF 2.0. In at least one instance the documentation for a function was non-existent. Second there are many places the videos can be cleaned up eg. transcriptions are just wrong like a machine did it, or the speaker repeats the same thing twice in rapid succession. Overall the course felt unpolished and dated.

автор: Ayush S

17 мая 2020 г.

The Face_recognition assignment was a tough one to solve, i only got grader problems but still i wasnt able to figure out how to pass grader even though my code yieded right answers. That's my only complaint otherwise the videos from Andrew were really easy to understand and the programming assignments were very well documented. Thanks :)

автор: Chris M

2 авг. 2019 г.

The assignments are less copy paste and some allow the student to explorer different NN architectures. However, most of the videos are still a waste of time. And the methods needed to complete the assignments aren't taught to the student. Instead you have to spend a lot of time searching and hoping you find the right method.

автор: André N

2 дек. 2018 г.

video courses were really good, but the programming assignments drove me nuts. I am a senior software developer and I am writing software for more than 10 years now. I had a really hard time understanding the Tensorflow code. I think it is better to suggest a student to learn the basics of Tensorflow before doing this course

автор: Tuấn T L

22 дек. 2021 г.

This course is well organized with CNN knowledge. However, it seems like the team is overwhelmed to maintain both a big Tensoflow tech stack in programming assignments while keeping academic science core concepts. Some code comments are outdated and the mentors definitely can not follow up all the issues raised by students.

автор: Mladen M

20 янв. 2020 г.

Couple of suggestions: 1) fix the artwork via neural networks assignment as there is a bug in your code 2) With the lectures I would suggest that you do a summary explanation of how the whole process works (all steps and motivation - a review) at the end of each group of lectures (one for artwork one for face recognition)

автор: Quoc B D

11 июня 2018 г.

The theory is very good but the exercise part is not good enough for me (For example in the Face Recognition exercise, I'd like to build (even a simple model) and train the triplet loss function... However, all that I can do is only loaded a trained model and then apply some simple similarity measure on encoding vector)

автор: Zach L

9 апр. 2018 г.

videos are excellent and insightful as always. I thought the homework assignments for this section were the worst yet. simultaneously holding your hand so much you don’t do or learn anything meaningful, and also providing you with obscure or insufficient guidance in the moments when you’re asked to fill in the blanks.

автор: Ernesto G d l P

11 апр. 2021 г.

There is major room for improvement on the automatic grader, under some particular cases, the answers are correct but the grader will give you zero with no feedback (in my case, I made a mistake with declaring local variables as global in the code). This issue is quite frustrating, the forums helped a lot though.

автор: Anthony M

4 дек. 2017 г.

Great class and amazing assignments. I really enjoyed learning about CNNs, YOLO, and Neural Style Transfer.

Errors with submitting the assignments, particularly weeks 2 & 4 took away considerably from the overall satisfaction with the course.

Thank you once again for providing a rich learning environment. :)

автор: Christopher C

9 сент. 2020 г.

Programming assignments were not to the level of the prior courses in the series. Should have more illustration of using Keras/Tensorflow. Assignments either were too spoon fed or there was too little reference information whereas prior courses had a good balance. Many of the keras links are dead.

автор: Luis F A

9 июня 2019 г.

Theoretical content was very informative and high quality. However, some problems with the programming assigments were annoying. For instance, for the last programming assigment some weights would not load and it was necessary to go get the weights from the github repository of some other person.

автор: Shreyash W

6 янв. 2020 г.

The week 1 and 2 were perfect, then week3,4 had some issues with the lectures- Andrew sir was repeating some parts and the problems/corrections in the slides.Also the week3 object detection was tough n the hints were not enough, with the errors in the assignment submission costing me a day

автор: Achille H

6 июля 2020 г.

Great content, veerything is clear and concise. Only downside is the grading of the exercises, which sometimes requires you to use a very specific syntax (even though another syntax gives the exact same results) and causes hours of painful debugging and reading through the forums.

автор: Patrick C N

2 февр. 2020 г.

Model implementation is abstracted in many exercises. Many helper functions are created to just make things work. TensorFlow feels a little foreign still, not enough of an overview. Higher level APIs like Keras and/or PyTorch might do better here instead of mixing in TF randomly

автор: Cristina B

7 февр. 2018 г.

The last two weeks sometimes bored me and sometimes I had hard time in doing the assignments. The intuition behin object detection/face recognition and neural style transfer are well explained, but some more details for understaing how these models work is missing in my opinion.

автор: ALEXEY P

28 июня 2019 г.

The lecture content is good but the programming exercises are not explained well. Quite often you are left on your own to go through Keras and TensorFlow documentation. So, don't expect much help in learning how to implement the theoretical ideas explained in lectures.