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

4.9
stars
42,029 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

AV

Jul 11, 2020

I really enjoyed this course, it would be awesome to see al least one training example using GPU (maybe in Google Colab since not everyone owns one) so we could train the deepest networks from scratch

OA

Sep 3, 2020

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.

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5351 - 5375 of 5,570 Reviews for Convolutional Neural Networks

By Amit A

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Sep 2, 2020

Andrew Sir explanation is awesome, but please do explain concepts in videos also, as some programming assignments contain data, info that we are not having knowledge

By Sebastien M

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Aug 1, 2018

I spend 1 week on the last assignment due of one bug. I am disappointed but the content of the course was good. Please next time react faster for correcting bugs

By Stanislav C

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Jan 29, 2018

Grader in the last assignment is wrong. It has been reported in the discussion forums several months ago and still hasn't been. Apart from that, great content

By Jesus A F

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Jan 20, 2018

The course gives you a good introduction to NN. However, the grading is buggy, and the content rather superficial. It gives you a false sense of achievement.

By Stefan M

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Jun 14, 2019

The homework assignments, compared to the other courses, where pretty low in quality. If these errors get corrected, I'd happily give this course 5/5 stars.

By Mathias E

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Oct 25, 2021

Videos were mostly great!

Expected more of the written material (quizes, assignments, etc.), not the quality I would expect from something I've paid for...

By Uddhav D

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Jun 7, 2019

Some issues regarding the submission of assignments and some minute mistake in the videos and assignment. Although great teaching by Andrew as always :)

By Karol K

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Dec 3, 2017

Issue with triplet loss function shouldn't happen. I had to remove "axis = -1" in order to pass grader even though function had produced wrong answer!!!

By Dmitry K

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Nov 30, 2017

There are a lot of issues with programming assignments grader (I've spent one hour to complete assignment and two days to make a grader to get it)

By Roel H

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Jun 22, 2018

The programming assignments contain bugs. Also the jupyter notebook kept on shutting down thus slowing down the learning process quite a bit :-(

By Kalana A

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Jan 25, 2019

Certain Parts are not that much clear. Specially like in the triplet loss function, until the coding was done the real procedure was not clear.

By Kanishka D

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Dec 27, 2017

the assignment setup and graders are not updated after reporting issues several times which caused a great deal of frustration among students.

By Felix P

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Nov 20, 2017

The last exercise it was a litle annoyng, it took me almost five days to figure out how to solve the face recognition because a grader fault.

By Sergio B

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Dec 13, 2020

I enjoyed the courses but I would like more practice, maybe a different module or examples aimed to help you define and optimize our models

By Serkan Ö

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Jun 10, 2018

There were repeats in the videos🤔 Also the answers to quizzes are not visible. If these would have existed, 5 stars would be reasonable.

By Reyrey

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Mar 17, 2018

Sometimes it was very difficult to understand lecturer because of his accent, but apart from that, assignments and lessons were helpful

By Stephen D

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Mar 17, 2018

This course is pretty good. Some things are not explained as well as Prof. Ng typically explains things, especially in the last week.

By Carol S

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Jul 19, 2020

The Neural Style Transfer notebook seems to have makes it difficult in the last panel to access the generated_image global variable.

By Jkernec

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Jan 12, 2018

The assignments need to be reworked as they are quite confusing and the grading system is flawed especially for the last assignment.

By Jnana R D

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Mar 13, 2019

More simple lectures with illustrations required and also graders need to fixed. Had a lot of time wasted because of buggy graders

By VORA N

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Jun 11, 2020

It has very less explanation about working of back propagation of convolution network,

plus it can explain YOLO in much better way

By Aoun L

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May 29, 2018

The course is great but the assessments and grading is terrible, so many particularities and repetition that does not make sense.

By Sudhanshu D

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Apr 8, 2018

Week 3, exercise 2 is very buggy. Couldn't have completed it without the discussion forum. Kindly fix it for the future learners

By Ankit R

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Oct 7, 2019

Found it really difficult to submit programming assignments, at times the jupyter notebooks were not at all responsive.....

By Gowdhaman S

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Apr 22, 2018

Course content was good but lack with hands-on projects. It would be really helpful if the team could add capstone project.