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

4.9
stars
42,232 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

SH

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Great content in lectures! Automatic graders for programming assignments can be tricky, and set to old versions of tf sometimes, but answers to these issues are readily found in the discussion forums.

FH

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Amazing! Feels like AI is getting tamed in my hands. Course lectures , assignments are excellent. To those who are not well versed with python - numpy and tensorflow , it would be better to brush up.

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1951 - 1975 of 5,600 Reviews for Convolutional Neural Networks

By JohnKyens

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Dec 23, 2017

The instructors are great!Very GOOD teaching to tell you complex DL technology

By Greta B

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Nov 17, 2017

I liked all the learning material and assignments as well. Very helpful course

By Siri K

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Oct 6, 2023

Best Course to ever exist on the internet on Convolutional Neural Networks!!!

By kaleem u

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Feb 11, 2023

Best content delivered in an easy and interactive way by Professor Andrew Ng.

By Linh P

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Oct 2, 2022

Excellent Course. The material covers a lot of grounds on understanding CNN.

By Rustam F

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Jan 30, 2022

Very practical, explanations are very intuitive and clear, exercises are cool

By Lihong Z

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Aug 12, 2020

Very detailed and clear explanation, and perfect designed hands-on practises.

By Christian G H

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May 25, 2020

Very good. Being able to understand and use state of the art models is great.

By Jaap d V

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Apr 2, 2020

This one was harder but a lot of fun, I liked doing the neural style transfer

By Ivan

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Jan 9, 2020

Amazing course, tons of useful insight, Big thanks to Andrew Ng and the team.

By Diego A B T

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Jan 8, 2020

Excellent, the best course of the specialization. Some videos must be edited.

By Nitish S

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Nov 26, 2019

Extremely useful introductory course for anyone interested in computer vision

By Qingyun W

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Jun 14, 2019

It will be nice if some of the programming exercise issues could be resolved.

By Karel N N

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Apr 5, 2019

Excellent courses, and a great teacher! Best regards and thank you very much!

By Mohit T

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Jul 19, 2018

Great course. Exercises are awesome and Andrew's teaching is one of the best.

By Edir G L

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May 14, 2018

This the best course in Coursera I've done. I learned a lot from this course.

By Patrick E

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Feb 17, 2018

Gives a very good understanding of ConvNets and the practical implementation.

By Zephyr L

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Dec 4, 2017

very easy going! Thanks for the team's dedicated efforts on the exam setting.

By Gaston M S R

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Dec 3, 2017

Great Course

Thanks to Andrew NG ans his team for another outstanding course!

By Victor C

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Dec 2, 2017

Andrew is excellent. Lectures and assignments are effective and challenging.

By Fabio B

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Nov 10, 2017

Very interesting and important course to take. I encourage anyone to take it.

By YASIN M

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Nov 5, 2017

Andrew Ng is awesome !!!! Love his teaching, course design, assignments, etc.

By Stanley P

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Nov 3, 2017

Thanks Andrew Ng. This course helps me to understand and practice CNN better.

By FAIQAZHAR A

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May 7, 2023

A great course about the mechanism of CNNs and various algorithms using CNNs

By Mohamed K

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May 1, 2023

w1 and w 2 were a master piece but w3 maybe it needed some more explanation