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

4.9
stars
42,028 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

RK

Sep 1, 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.

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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501 - 525 of 5,570 Reviews for Convolutional Neural Networks

By Phan Q K N

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Feb 18, 2022

It was such a great course. I got a chance to study and apply fundamentals of ConvNet to many practical problems such as Face Recognition, Object Detection, Semantic Segmentation, Neural Style Transfer which I have longed for knowing.

By Veeraraghavan N

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Jun 14, 2020

The course is really good with in-depth explanations of the concepts in a clean, clear and precise manner that is both easy to understand and implement. The programming assignments are fun to complete and test out. Highly Recommended!

By Raymond S M

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Jun 25, 2019

I found this to be an excellent introduction to convolutional neural networks. I was already very familiar to convolution but I could see that if I wasn't it would have been clear. All concepts were explained well and I learned a lot.

By David R V O

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Mar 10, 2019

I think this course is excellent and I'm already applying the skills I've learnt from it to my current research. I would have preferred a little bit more focus on the theorical part of ConvNets, especially backprop. 100% recommended.

By Zifei S

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Feb 20, 2019

Very clear lectures and hands-on experience to gain lots of experience with CV problems and cutting-edge models. I'm an NLP engineer and this course gives a great intro to DL for CV. IMHO it's one of the greatest course in the series.

By Dao M C

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Mar 3, 2021

Thank you very much Andrew Ng. The course helps me understand very well about Convolution Neural Network. Lectures go from easy and then combine together, even assignment, I feel very excited and happy to learn in the teacher's way.

By Devavrat S B

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May 26, 2020

This course is very good if you want to enhance your knowledge about CNNs, the course contains different CNN architectures and use cases, the way Andrew Ng Sir teaches every concept in detail along with visualization is appreciable.

By Yuezhe L

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Nov 19, 2018

This is an immensely helpful class. I have been wanting to learn imaging processing and machine learning, and this class helps me get started. Using what I learnt from this class, I was able to implement CNN to help my own research.

By Taras M

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Jul 29, 2018

The most interesting course in the whole deep learning specialization, a lot of practical cases and much closer to the deep learning state of the art. Kudos for face recognition and neural style transfer (yolo is super cool as well)

By Ahmad J

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Jan 26, 2021

Fantastic overview of CNN's from a historical perspective but also from a practical and theoretical perspective. Basically all facets of CNN's have been very clearly discussed. Andrew Ng is just a pleasure as a teaching instructor.

By Li W Y

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Jan 8, 2018

This is a great course which make me know how to do computing vision and neural style transfer (which is something I thought amazing before). Although the course is a bit difficult, it is interesting and useful. Hope you enjoy too.

By Stuart H

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Nov 30, 2021

I found this more challenging than the previous courses, but learned a lot. The concrete examples of CNNs were really helpful to picture how they are built in practice and the exercises helped me understand tensorflow much better.

By Azmyin M K

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Nov 29, 2020

Week 3 was most relevant to my work on Indoor Positioning System. I felt like week 4 could have been made optional. Other than that, excellent material, easy to understand and digestible for us students from engineering discipline

By Gautam D

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Jan 11, 2019

Wonderfully explained! Andrew and team have been kind enough to provide all the important papers and documentation required too. Very well laid out course. Can't wait to finish the 5th and final course! Thanks team deeplearning.ai

By Bhaskar G

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Sep 26, 2018

An optional course on Tensorflow/Keras and their comparison with other prevalent frameworks would have given a nice touch. I realized that lot of handholding is needed in assignments just because the basics if TFlow are not clear.

By 胡帆

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Feb 27, 2018

Excellent course! And the programming assignment is necessary if you want to know deep learning deeply, the video is shallow and it is more like an introduction to deep learning . Anyway, Andrew Ng is absolutely a great teacher!

By Jack Q

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Jan 31, 2018

This course offers quite plentiful materials. I learned lots of models whose performances are state-of-the-art. Brief and intuitive description of these models helps me a lot when reading the corresponding research papers. Thanks!

By Ernesto S

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Dec 20, 2017

I love how the content of this course is structured. Also love the fact that all the weeks contents can be found within the exercises themselves. Thank you to all the people that worked so hard to deliver this exceptional content!

By Siddharth P

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May 24, 2020

A very well presented course that covers a good breath on different types of CNN model to date. The exercises are good, given the computational limitations, it is understandable why most of the exercises used pre-trained weights.

By Makarand D

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Mar 19, 2020

A more consistent Keras or Tensorflow workflow would be good. I passed all the assignments but still feel unclear abotu Keras and TF workflow. But that will come with practice. Great teaching in terms of conceptual understanding.

By Zhoutian F

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Apr 15, 2018

The course is really helpful to beginner. However, I really suggest to add more introduction of modern CNN networks to this course, such as R-CNN for semantic segmentation. Really appreciate Prof. Ng and Coursera for this course.

By Jose G P R ( B

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Dec 19, 2017

Step-by-step convolutional networks are presented. It is excellent learning to construct the convolutional networks in the lab. I read too much about these type of neural networks, but no one has me shown before how to build them

By nitin k k

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Dec 15, 2017

great explanation, great examples , great assignments , nice support and the most important thing is how easily andrew sir has explained the complex topics of deep networks . Its an honor to learn from such a great mentor. Thanks

By Jean M A S

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Dec 10, 2017

It's surprising how the team deeplearning.ai stay consistent in the quality of the course given. Highly recommended. Maybe the best course in the specialization so far, Pr Andrew Ng has a gift to make something complicated plain.

By Pushpendra G

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Oct 3, 2020

We can not describe how awesome these courses are! We are very much fortunate to see these time where everything is available and high-quality material can be accessed from anywhere. Thanks to Coursera Team and to Andrew Ng Sir.