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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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4776 - 4800 of 5,570 Reviews for Convolutional Neural Networks

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 Erik 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.

By Nitish K

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Apr 21, 2018

Neural Transfer and Object Identification (YOLO) was not explained very well. I had to look out for external videos on Yoututbe to understand YOLO.

By Meriem S

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Dec 3, 2017

CNN is not only used for image processing. It can be used in other fields. I hope so we can find other case study than image processing. thank you

By Wu Y

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Jan 7, 2019

Week 3 has a bad grading system for the programming assignment. The exact "0" blocked many time, and waste efforts. Otherwise, the course is good.

By Jk L

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Dec 17, 2017

It would be better if some gpus were provided, or the experiments of style transfer were a little painful. Anyway, the course itself is wonderful!

By Georgezhu

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Apr 7, 2021

Pretty good! Although this class is very good and easy to learn, something in this course is so simple that some key points are not well claimed.

By Suchitha L D

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May 26, 2020

Good content but the labs should be upgraded to Tensorflow 2. Some quiz questions are bit vague and feedback isn't helpful to understand mistakes

By mahdichalaki

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May 26, 2020

Some videos are not carefully edited and there the teacher repeats some sentences.

But overall, the materials and of course Andrew Ng are perfect.

By Arturo M R

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Aug 29, 2018

Assignments are not always consolidating acquired knowlegde, due to the distance between implementation from scratch and using predefined models.

By Michalis F

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Feb 16, 2018

Very nice course.

assignments are very high level though and just help in giving a taste of convolutional neural networks.

lecture notes are great

By Roberto J

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Nov 21, 2017

A bit buggy some of the exercises, some of the videos and some of the course notes, but the material is excellent and the learning is invaluable.

By Galley D

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Dec 2, 2017

Amazing course that breaks down the complexity of CNN

Some assignment have issues yet the forum displays significant resources to help solve them