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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

AG

Jan 12, 2019

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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4701 - 4725 of 5,570 Reviews for Convolutional Neural Networks

By Renjith R K

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Dec 8, 2020

Andrew Ng's simple explanation of complicated concepts lets you grasp concepts that require hour-long reading of research papers in a few minutes, Assignments could be more elaborate.

By Lennard S B

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Jul 12, 2020

Der Kurs hat mir sehr geholfen und war Zeitlich gut zu schaffen.

Bei den Programmieraufgaben hätte ich mir ein paar beispiele gewünscht, um schneller in die Syntax einsteigen zu können.

By Tulip T

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Sep 13, 2019

It can be so much better if Andrew covers some more overviews. But it is still a great course and everyone should take it. Andrew gives the most understandable lessons about Yolo ones.

By chandrashekar r

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Feb 6, 2019

The first week was good and well presented. From the 2nd week onwards it as very cryptic. In the final week, on what are deep conv nets are learning, more details could have been given

By Tristan G

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Nov 22, 2018

I feel some of the theory was rushed here and high level functions used instead of explaining some of the more difficult concepts in the papers referenced, such as the Inception paper.

By Thomas C

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Jul 11, 2018

Good course, gives you a rough overview of popular CNN architectures and the basics of how they work. Assignments are easy but give you a chance to apply some of the stuff you learned.

By Arun

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Jun 12, 2018

The content was great, as usual, from Prof. Ng. But I wasted a lot of hours trying to make the programming assignment submissions, since auto save in IPython Notebooks kept on failing!

By Boyu L

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Feb 1, 2018

Minus one star for the assignment issue (triplet loss) for Week 4, this is a bit beyond acceptable considering how long the issue has evidently been there. Otherwise, stellar content.

By andrew w

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Feb 7, 2021

Excellent content and explanations as usual. A small criticism for this course compared with the previous three is that the videos have clips of repeated content due to strange cuts.

By Debdeep P C

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Jun 13, 2019

Course content was good,but grader needs to be updated as in many cases I had to submit assignments manually by uploading it,as the grader wasn't working.Everything else was good. :)

By Alysha R

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Jan 3, 2018

Weird grader error on the week 4 assignment in triplet_loss function -- had to put axis=None instead of axis=-1, which is wrong (and contrary to the directions) -- needs to be fixed.

By Cristian M V V

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Mar 21, 2021

Great course. Very good and simple explanations of complex topics. The 4 is just for the sake I hoped for a deeper dive into Tensorflow and how everything changes with Tensorflow 2.

By Pablo C

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Dec 1, 2017

The problem with the triplet loss function and the grader was not solved until Dec 1st. This was misleading me, and, in order to grade fully I wrote a wrong version of the function.

By Guenther W

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Jul 24, 2020

A clear presentation of difficult problems and I love working with the notebooks. However meanwhile most of the tensorflow documentation hyperlinks within the notebooks are broken.

By Paul F G

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Aug 21, 2019

This course was of the same high quality and detail of the first three, but the last project was difficult due to bugs in the python code. This definitely needs to be fixed please.

By Anushan F

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Feb 4, 2018

The grader didn't work correctly on the final assignment. Course content was both really interesting and well explained though. Thanks very much for putting together these courses!

By Yan F

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Dec 10, 2017

The content and lectures are still great. But the assignments and graders have a few bugs. I guess it's because of the insufficient preparing time. However, I did learn what I need

By Philip L

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Jul 24, 2019

The lectures were excellent, but many of the exercises and quizzes had "issues" that wasted a lot of time. You need to spend a LOT of time on the internal forums for this course.

By Jakob E

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Jun 2, 2019

Great content and superb videos. The assignments are becoming exponentially more challenging if one is not familiar with Tensorflow as the intro on that framework is rather short.

By Alon M

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Dec 10, 2017

great lectures.

yet there are some places to improve :

1) the assignment are harder (which could be good) yet they are hard by being less clear

2) there are some bugs in the grader

By Robert C

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Jun 1, 2020

Good content, I learned a lot. Just one thing, the programing assignments need to be updated to tf > 2.0. Currently running 1.2.1 (released on Jun 30, 2017) in week2 and week4.

By Amit R

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Jan 29, 2019

I wish to rate this 4.5 out of 5. Some descriptions (eg: YOLO alogrithm) are less elaborate or may be I found it difficult to understand. Overall, it is a very good course. :-)

By Keith N

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Nov 30, 2017

Good course but lots of technical issues with grading of programming assignments. Did not see these issues in previous courses. Maybe more background on tensorflow is needed.

By Haosen G

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Jan 20, 2021

A bit difficult for people who don't have too much coding experience, especially those who are not familiar with using open-source packages, reading documentation by their own