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Learner Reviews & Feedback for Convolutional Neural Networks by DeepLearning.AI

4.9
stars
42,232 ratings

About the Course

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....

Top reviews

DD

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very easy to understand and helped my understanding in Deep Learning-based computer vision. Yet, this course will need to be updated with new developments in the future (to catch up with the trend).

SH

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Great content in lectures! Automatic graders for programming assignments can be tricky, and set to old versions of tf sometimes, but answers to these issues are readily found in the discussion forums.

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5526 - 5550 of 5,600 Reviews for Convolutional Neural Networks

By Alex S T

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Nov 9, 2018

The first two sessions are very well explained, with clear and precise examples. However the last two sessions, are explained in a very superficial way, without a good example, the explanation of these sessions are not deepened, the practical exercises don't teach how the problem is really solved. To truly learn, it is necessary to go out searching the internet.

By Kees J K

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Sep 22, 2022

The content is good, but the videos have not been edited properly. There are spoken notes to the editors left in the video and you can hear Andrew rephrase sections. To me that is really distracting, as I now start thinking about how Andrew phrases things, instead of about machine learning.

So a good beta. but certainly not a finished product.

By Jonghyun K

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May 5, 2020

The subject of the lectures are good. However, Andrew's voice is still relatively small with other noises.

Also, there are quite a lot of times when same words are repeated in the audio.

Finally , during the lecture a felt a little bit of sinocentrism from Andrew.

By openrasmus

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Jul 26, 2020

Multiple of the videos have editing issues and repeat clips. Programming excercises were good, but final programming exercise was a pain to finish, not cause of difficulty but cause of having to debug code without any proper feedback on whats wrong.

By HAMM,CHRISTOPHER A

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May 26, 2018

The lectures were taught far above the heads of my colleagues and I and the practical exercises were far too simple. I really wish the instructor took a course on pedagogy or went through Software Carpentry instructor training.

By David C

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Dec 24, 2017

Week 4 videos were not edited at all. Week 4 lecture slides were not available for download. Week 4 programming exercise grader had significant errors such that the incorrect solution needed to be coded in order to pass.

By Stoyan S

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Jul 29, 2018

Some of the topics were not explained in enough detail and felt like being quickly skipped. There were some problems with the grader system in one of the assignments which wasted a lot of time and caused frustration.

By Bryan L

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Jan 21, 2018

Content was great but a very buggy grader in week 4 made for a stressful experience that upset many students. Grader bugs caused me to repeat the course in another session and those bugs remained in the next session.

By Oswaldo B F

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Dec 1, 2017

Programming assignments did not deal directly with the CNN models, but with auxiliary functions. Hacking the grader was more important than getting the right answer. Videos should have been better edited too.

By Vihar K

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Jun 6, 2018

Lectures are awesome, really inspiring and intuitive.Trouble with submitting assignments. I've solved the given question and resubmitted for almost six times, but the kernels showing up errors.

By Carlos K

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Jul 12, 2018

Horrible user experience with the "Jupyter Hub" constant issues that makes trying to do the exams an absolute nightmare and a perfect anxiety booster!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

By Dario d J B U

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Nov 15, 2019

In some tasks the delivery format is arbitrary and does not specify well what is wanted, that is, so the numerical value requested is good, the output is incorrect. due to format issues.

By Aman B

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Jul 23, 2020

Programming part was not explained well. I guess programming syntax and flow of code should be explained too instead of just telling theory or focusing mainly on theory.

By Daryl V D

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Jun 19, 2018

TOO MANY BUGS IN THE EXERCISES.It was a dis-incentive. Really.And I love me some deeplearning.ai! It has been great. The videos and content structure are fantastic.

By Arsh P

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Dec 15, 2018

Though the videos were very good but the assignments require too much from us and also there are few mistakes in week 3 and 4 notebooks which take a lot of time.

By Yongseon L

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Jun 15, 2019

https://www.coursera.org/learn/convolutional-neural-networks/programming/IaknP/face-recognition-for-the-happy-house/discussions/threads/NcpP7i95EemJswr-eOHMNg

By mike v

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Jun 8, 2019

The content is excellent, but there were technical problems with the final homework assignment that were not addressed by staff in a timely manner.

By Sébastien C

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Aug 18, 2020

Content was interestind and provided good theoretical overview. Exercices where you just have to fill in some line of codes are not usefull.

By Joshua S

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Nov 29, 2019

Some of the code was incorrect and the guidance was often confusing. Visibly worse than the other courses in the specialization,

By Kristoffer M

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Nov 30, 2019

Don't feel like I understand these models much better than before. Still don't see the logic of the identity layers

By Prasenjit D

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Dec 6, 2017

Lots of problem with the grader. Wasted a lot of time grappling with grader issues. Very disappointed.

By Sandeep K C

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Dec 28, 2018

The quality of some of the graders e.g. IOU is poor. One cannot make out what exactly is it checking

By I M

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Oct 17, 2019

Disappointed by the quality of notebooks, which often disconnect and lose all the code you wrote.

By Shuhe W

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Jun 8, 2019

The course assignment parts have many errors, I have to fix it myself. That's silly.

By Bernard F

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Dec 13, 2017

Good content, but quite a bit of technical work is needed to present this better.