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

4.9
stars
36,185 ratings
4,671 reviews

About the Course

This course will teach you how to build convolutional neural networks and apply it to image data. Thanks to deep learning, computer vision is working far better than just two years ago, and this is enabling numerous exciting applications ranging from safe autonomous driving, to accurate face recognition, to automatic reading of radiology images. You will: - Understand how to build a convolutional neural network, including recent variations such as residual networks. - Know how to apply convolutional networks to visual detection and recognition tasks. - Know to use neural style transfer to generate art. - Be able to apply these algorithms to a variety of image, video, and other 2D or 3D data. This is the fourth course of the Deep Learning Specialization....

Top reviews

RK

Sep 02, 2019

This is very intensive and wonderful course on CNN. No other course in the MOOC world can be compared to this course's capability of simplifying complex concepts and visualizing them to get intuition.

AR

Jul 12, 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

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351 - 375 of 4,623 Reviews for Convolutional Neural Networks

By Gautam K

Jul 08, 2020

This course is awesome. It helps in learning CNN in a very easy way. Concepts are taught in a fantastic way that makes it easily understandable. Programming exercises are designed in a way that makes typical concepts easy and is based on practical applications.

By Anshul M

Apr 29, 2020

The concepts of CNN and the attached algorithms have been explained clearly. I found the programming exercises to be one of the best way in order to get a first hand experience over implementation and understand the concepts required to build my own application.

By khalid w

Nov 10, 2019

This course has helped me very much in understanding the nomenclature of convolution networks. Previously I struggled reading different research papers related to convolution networks as I was unable to understand the different dimensional changes in each layer.

By Oleksiy S

Dec 20, 2018

Exellent course for first experience with convolutional networks. A few mistakes that seem frustrating at the time you are completing course really help to gain better overall understanding. Thanks a lot for good work all the involved people, stuff and mentors.

By Sayar B

Aug 16, 2018

Perhaps the toughest course so far, Convolutional Neural Networks introduces us to computer vision. Professor Andrew explains complex, state-of-the-art cases where computer vision is being used today. Great programming assignments, great lectures, great course.

By Shifeng X

Mar 25, 2018

awesome course! the assignment is actually not just a piece of homework, it indeed a kind of guidance, give you detail step by step examples of how to code the learned algorithm. Thanks to the lecturer, didn't find any course more 'user-friendly' than this one.

By Abel G

Nov 07, 2017

Wow.. what Can I say? This was the toughest of the three previous but super happy to be in this journey.

I learned a lot and I am motivated more than anytime to immerse myself in this field. There is so much to learn. Thanks to all the people behind this course!

By Ruby A

Aug 23, 2020

Excellent explanations of the theory and math behind the basics of CNN that anyone can understand easily. The assignments are also well designed in such a way that one could apply the theoretical knowledge gained to solve real time problems. Excellent course.

By Karthikeyan R

Dec 29, 2019

Again, excellent course from Andrew Ng! Made complex algorithms and concepts very clear! Got to know how CNN, Facial recognition and Object detection works. Reference to the literature paper will come handy in the future if one thought of diving deep into CNN.

By Julian S

Nov 20, 2017

Excellent course. Concepts very clearly described. Only improvement would be more Tensorflow and possibly Keras training. Yes, you can go elsewhere for this, but Andrew Ng is so good at explaining, I'd expect he'd do a better job!

Many thanks Mr Ng and team!!

By Reda M

Apr 07, 2020

Excellent course ! Theory and practice are covered in a relevant way, and Andrew's been very encouraging and clear all along this CNN journey ! The fun part is obviously art generation with the VGG19. Great thanks to Andrew and to the deeplearning.ai team !

By Yao F

May 20, 2019

The course is pretty good with advanced techniques on computer vision. The only regret is one problem about the last coding homework. I failed to load the pre-trained model and can only finish the home work without checking the accuracy of designed examples.

By Pankaj D

Dec 26, 2017

Amazing course plan and delivery! Classic CNN architectures, ResNet, YOLO, face-recognition, neural-transfers - all in a very succinct package! Some very minor issues with auto-grading of assignments, but nothing that the discussion forums won't get you thru.

By Jayaram R

Jan 28, 2019

Andrew's explanations, and the exercises are absolutely fantastic. There seems to be a lot of tricky math in Convolution Neural Networks and Andrew's explanations and illustrations help students understand the essential concepts behind each type of Conv net.

By Paul S

Nov 29, 2018

Excellent course. Very good and well structured explanations by Andrew Ng: one concept per video, sometimes a second video to explain why the concept works or to give some intuition. Course covers many of the classis deep learning papers. Highly recommended.

By Joshua P J

Aug 07, 2018

Weeks 1 & 2 were very good. Week 4 was excellent with extremely clear presentation. I didn't like week 3; it felt like the topics were presented in random order, and the homework felt trivial (I finished it easily but I still have no idea what was going on).

By Camila B V

Mar 25, 2020

Awesome, I loved taking this course, the way to explain the topics is the best. I enjoyed every part of this course and the most important part I understanded several concepts. The exercises and material class are really usefull. Congrats you're the best.

By Kaan A

Jul 30, 2019

This course was the greatest one among the first 4 courses of the Deep Learning Specialization. Real world examples were perfect. Moreover, the paper suggestions helped me a lot to learn through my process of this course. Thank you Andrew and Coursera Team.

By Michael G

Nov 16, 2018

Great examples and walkthroughs. I didn't think I would be able to code all the various CNN architectures, but this course made that process challenging, but doable. Now it is time to start working on side projects to sharpen the skills I have learned here.

By Artem P

Apr 22, 2018

Probably the best course in the specialization (well, along with Sequence models). 50 layer VGG model built in Keras gives awesome enterprise-level results on a relatively small data sets..! But I recommend taking all these courses, they are all very good.

By Guillaume G

Nov 15, 2017

I really like how Andrew Ng is able to explain actually pretty complex concepts in a comprehensible way, built on the knowledge of the previous weeks content.

Also great is the integration of recent techniques: inception modules/networks, residual networks.

By Amit A

Dec 27, 2019

Excellent course. Professor Andrew Ng ensured easiness in following the courses, highlighted important aspects and the assignments were very well structured. I am glad to have taken up this course and I hope to start using my learning in the coming months

By Chetan P B

May 08, 2020

Amazing!! The assignments very well cover the concepts taught in video lectures and each part of the convolutional network is explained in detail. The First 2 weeks are quite full of concepts. I enjoyed the last 2 weeks covering the applications of CNNs.

By Daniel J D

Jan 04, 2019

Andrew Ng's courses and Geoffrey Hinton's are about as good as courses get--rigorous, practical, and yet fairly thorough in the underlying theory. Convolution Neural Networks is certainly no exception to that as he goes into res nets and inception nets.

By Yu G

Nov 03, 2017

It's really a great course that I've waited for so long! Thanks a lot for providing the well-organized and easy -understanding materials for those new starters of deep learning like me! Hope to see the last part of sequence models in the nearly future!