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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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1926 - 1950 of 5,600 Reviews for Convolutional Neural Networks

By Shuangqi

Aug 2, 2018

It contains many example of the CNN models that can be used for Computer Vision

By Mohit J

Jun 10, 2018

Great Course! Learn so much, that was not available in any other online course.

By 徐超

Jun 6, 2018

I learn a lot about intuition and details in this course, really good lectures!

By lun c

May 9, 2018

Great course! Learned skills for building driverless car and face recognition!

By Julien L

Apr 17, 2018

Very good course with good application examples and state-of-the-art algorithm.

By Daniel V

Dec 30, 2017

The teacher is awesome and the projects really cool and help you improve a lot.

By Paulo F

Nov 26, 2017

Awesome explanations. It touches the major concepts to develop/understand CNNs.

By Iosif D R

Nov 8, 2017

Very instructive. Simply brilliant way to explain quite cumbersome mathematics.

By timmy

Aug 3, 2021

Concepts are clearly explained. Weekly assignments are practical and on point.

By Mina H

Oct 17, 2020

Such a great course. Thanks to all the people who are trying hard in Coursera.

By Abhishek S

Oct 16, 2020

Exceptionally well designed course, with an amazing teacher and great content!

By Yaolin G

Apr 9, 2020

Super useful and easy to understand, very fruitful and rewarding. Thanks a lot

By Andrey A

Apr 8, 2020

One of the greatest introduction courses about computer vision. Thank's a lot!

By Andrew C

Feb 24, 2020

As usual, Professor Andrew can always offer excellent instructions. Thank you!

By gayatri l

Jan 30, 2020

Best experience.Broder my views and thinking.Happy to go in deeper and deeper.

By Risheeka S

Nov 23, 2019

A very important course if you want to begin solving computer vision problems.

By Chien D

Sep 8, 2019

This is a very well explained course. I cam earn a lot of practical knowledge.

By Mashrur M

May 21, 2019

Really gives you a lot of things to think about and work on. Excellent course.

By Xuecong L

May 8, 2019

Very informative, with good practice assignments! The interview part is great!

By Andrei K

Jan 25, 2019

I improved my knowledge in CNN, so I learned new CNN architectures. Thank you!

By David B

Jun 4, 2018

Great topic and easy to follow and then reproduce on your own. A great course!

By David H

May 9, 2018

The most exciting of the four courses so far, now looking forward to course 5.

By maluge p

Apr 10, 2018

Its a well organized course and the knowledge obtained from it is exceptional.

By steven c

Apr 4, 2018

The details of RCNN, fast RCNN, faster RCNN might be one session of the course

By Hiroko O

Mar 11, 2018

Thank you for the amazing lecture!

I really enjoyed the interesting assignment.