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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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2026 - 2050 of 5,600 Reviews for Convolutional Neural Networks

By Sergio B

Jan 12, 2020

Excellent course to understan CNN in depth, learnt a lot from this, thanks

By Stefan S

Jan 3, 2020

Highly complicated topic very well presented, a lot of applicable content.

By Akash G

Mar 20, 2019

The course was not in detail in terms of math and concepts. Like ML Course

By Krzysztof W

Feb 15, 2019

Great course, however the programming assignments could be a bit harder ;)

By Jeffrey V V

Jan 14, 2019

I learned a lot about the current state of the art convolutional networks.

By Aakash B

Dec 1, 2018

Great Course a must do for anybody who wants to get into computer vision!!

By Kuber R

Oct 21, 2018

This is the best comprehensive course about Convolutional Neural Networks.

By jozze

Sep 18, 2018

Very interesting course. CNN´s have seriously hooked me into the DL world!

By Sanjeev U P

May 3, 2018

Good introduction to CNN's as well as an providing intuition behind ideas.

By Jesús P

Mar 14, 2018

Great course! I think it can be improved with more architectures of CNN :)

By Douglas T

Jan 30, 2018

Excellent course. Learn a ton about CNN and various network architectures.

By Troy C

Feb 27, 2024

Very practical and engaging into to CNNs and the technologies they enable

By Malay M M

Nov 7, 2021

This was the course i loved the most in the Deep Learning Specialization

By João H

Sep 29, 2021

Very super informative, complete and fun course! I strongly recommend it!

By Vaibhav S

Feb 5, 2021

A truly perfect course! Just make the assignments a bit tougher, I guess.

By Itamar d P R F

Aug 19, 2020

Great course. Anyone interested in CNN's should do it. Definitely a must.

By coen h

May 5, 2020

Gives you a very good overview and some useful practical insight in CNNs!

By 曹杰

Apr 20, 2020

Great Lectures, covering the core ConvNet architectures and applications.

By Gerald C

Apr 13, 2020

Awesome, I will continue with further courses provided by DeepLearning.ai

By 徐雨臻

Jun 26, 2019

Excellent course. It is easy to understand the machanism, I learned a lot

By Thomas H

Feb 11, 2019

Great course but the exported slides are quite bad with overlapping texts

By Santiago I C

Feb 8, 2019

Perfecta continuación y muy interesante (y dificil) trabajar con imágenes

By Vu N M

Oct 25, 2018

I like this course, it gave me a lot of hint about the research direction

By Raihan K R

Aug 29, 2018

Among all the Deep Learning Specialization courses, this one is the best.

By Minglu Z

Aug 11, 2018

So many implementations in assignments!

Also harder than previous courses.