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

4.9
stars
42,319 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

RS

Dec 11, 2019

Great Course Overall

One 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.

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4801 - 4825 of 5,613 Reviews for Convolutional Neural Networks

By Collin J

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Sep 15, 2018

Could use more clarification/direction on the programming assignments. Also would be interested in learning more about how back propagation works with CNNs.

By Tianqi T

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Jun 19, 2019

the content of this course was very interesting and practical. however towards the end (week 4), there were a lot of confusions about how TensorFlow works.

By Pieter N

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Jan 15, 2018

Excellent course. My only reason for not giving 5 stars is purely because there was a grading error on the last weeks' assignment which is still not fixed.

By mihai.ionut.aurel@gmail.com

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Dec 4, 2017

Really insightful. I did the course on Udacity and didnt understand much about the CNN but now I feel I have a better understand. I can't wait to apply it!

By Hao Z

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Dec 2, 2017

The bugs in the grading system make me uncomfortable. People have to submit the answer which is obviously wrong but favored by the grader to pass the test.

By Hamlet B

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Nov 19, 2017

The content was fun and very useful. The last programming assignment had some incorrect guidance and made the grading experience unnecessarily frustrating.

By Jose-Luis L

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Nov 26, 2019

The course is great. There is only one minor downside: sometimes the notebooks' connection is lost and you lose the latest modifications of your homework.

By M J

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Jul 2, 2019

A good introduction to CNN's if you haven't seen them before. Strong on concepts and motivations. Kinda vague on mathematical details and implementations.

By preethi v

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May 6, 2018

The course structure is really good. But please do fix the bugs in the assignments. Thanks to the discussion forum, it helped me a lot in fixing the bugs.

By Sudipta C

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Jan 1, 2018

Excellent content delivered very honestly by Prof. Andrew Ng. The course has some broken grader issues which need to be fixed to make this course awesome.

By Jonatan K

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Jan 6, 2020

explained very well

very interesting with andrew

the main problem with this course is bug fixing on assignments.. i lost alot of hours just because of this

By Kenji M M

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Sep 13, 2019

the last programming assingment has a lot of bugs as of 9/13/19 and was verry difficult to pass even though the actual code was very simple ti implement.

By Yash R

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Dec 24, 2021

It was a great course. Though the YOLO implementation part is a little confusing. Probably more implementation details could be covered in the lectures.

By Ameya G

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Dec 21, 2017

Course content was good and well structured. Some videos still need editing and grader for 2 assignments is faulty. Otherwise a very interesting course.

By Nazmus S

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Aug 4, 2019

ipython notebook fails often. It was a frustrating experience. There are many bugs to be fixed to run the homework problem submission process smoothly.

By itay k

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Dec 21, 2017

A great course! I would have gladly given it 5 stars, but currently, the assignment of week four have bugs and the notebooks tend to stuck or run slow.

By Venkat K

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Dec 5, 2017

A bit dense and fast-paced even for Prof Ng's usual standards - this course is drinking from a firehose, but a great hands-on introduction to ConvNets

By Nitish S

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Nov 7, 2019

Could have a better explanation of TensorFlow graphs in the assignments. The course is still very good and provides a solid conceptual understanding.

By Frank H

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Dec 17, 2017

Very interesting topics were covered in a quite comprehensive way. Only useful packages like Tensorflow and Keras were introduced only superficially.

By E P

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Nov 27, 2017

Another wonderful course by the team, even with a few bumps this is one of the best introductions to what the heck a convolutional neural network is!

By Adithya J A

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Aug 31, 2020

Great course and would totally recommend it. Assignments need a bit of work in terms of instruction clarity for use of certain tensor-flow commands.

By Pablo M P

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Aug 24, 2019

I learnt many interesting ideas about convolutional networks, however, the course needs to be checked by the staff. There are many bugs in the code!

By Jarek D

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May 19, 2018

Programming challenges in this course were less practical than in previous ones, and instructions sometimes a bit vague. Still recommend it, though.

By Md R R J

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Jun 25, 2020

The notebooks did not help much to practice skills received from video lectures. Specially last 2 weeks. Felt like translating formulas into codes.

By Ernst H

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Aug 5, 2019

Very good course. The assignments are too easy and I would be able to complete them without understanding the course material or what I am coding.