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

4.9
stars
42,300 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

AV

Jul 11, 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

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.

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401 - 425 of 5,610 Reviews for Convolutional Neural Networks

By Leonardo R C

Jun 1, 2019

This is a very interesting and fun course to take. You put into practice all the knowledge from previous coruses from the specialization and apply them in applications that are changing the world right now. As usual, professor Andrew explains every concept perfectly.

By Harold M

Nov 18, 2018

The best course by far in this specialization. This course covers all the important topics in Convolutional Neural Networks, face verification and face recognition.

You have to work very hard to complete it. Thus, it's a great challenge!

Thank you Professor Andrew Ng!

By Yoan S

Oct 5, 2018

These courses are VERY well put together and concentrate excellent concept in little time compared to taking the available Stanford CNN classes online which are verytime consuming for the same result. Andrew is motivating and makes difficult concepts very accessible.

By Xavier S P

Dec 19, 2017

The idea of inserting convolutions into the net and in the back propagation is really cool yet so simple to implement after watching those lectures. It makes sense why image simplification via convolution in layers can greatly help performance in a deep learning net.

By Harold J C O

Jun 7, 2021

This course is exceptional, I learnt important topics for the career path that I'm trying to build in AI, I appreciate to all the team of DeepLearning.AI for the effort creating this amazing course, I recommend to anyones that wants to know fully details about CNNs.

By Ching-Cheong L

Oct 25, 2020

Very great introductory course. Since I am not familiar with tensor-flow, there is still a gap for me to fully understand everything in the programming exercises. But this also lead me to a clear direction what's next to me, thanks for the team creating this course!

By Abhinav M

Jun 6, 2020

I really love the instructor. He is the best teacher and a mentor. He has taught me a lot. I was nothing in Deep Learning, but the way he taught me inspired me of deep learning and machine learning. Now I am seeking my career completely into it. Thanks to Andrew Ng.

By Arash A

Mar 15, 2020

Such an amazing course. Andrew is such a great instructor. Actually, it is thanks to this course and the whole Specialization that I'm making now my own career as Chief AI Scientist for a Health Tech Start Up.

I'm endlessly grateful to Andrew and this Specialization!

By 梁礼强

Apr 2, 2019

this course is pretty good,but the some of these techniques introduced in class are slightly out-of-date,such as yolo v2 and this version of neural style transfer. It's OK as an introduction, but it may be better to mention the latest or general version algorithms.

By Agniva M

Jul 5, 2023

The course was great and I would like to convey my heartfelt gratitude to Prof. Ng for making the concepts effortlessly understandable. The course has been almost like a foundation for every possible literature that exists regarding Convnets and their applications.

By Yebei R

Jul 1, 2020

This is an advanced course in the series since the convNet is more complicated than the plain deep neural networks. However, it is very helpful for people who wants to learn more about CNN and its applications on object detection, face recognition and verification.

By Nilanka W

Jan 14, 2018

This course taught how the latest computer vision systems works. The content is really great and the lectures and mentors have put a lot of effort in creating the assignments and notebooks, which are high quality. recommend to anyone who are interested in the field

By Nilkumar P

Oct 18, 2020

Learning from this course is like living in heaven for any deep learning student. Mr. Andre`s explanation is of each topic make to understand more about the topic and today I`m taking decision to take master in AI and I will try to learn and understand AI deeply.

By Rúben G

Oct 20, 2019

Through this course I understood how modern Computer Vision tasks are addressed with CNN. Also I learn that a CNN can be combined with a FCN. I further understand better the notion of the neural network and the advantage/disadvantage of having more or less layers.

By Hemant J

Jun 26, 2020

Thanks to Andrew Ng for very structured and easy to understand course designed on Convolutional Neural Network design, it really helped not only gaining the CNN understanding but it's application to solve image verification, detection and recognition effectively.

By Michael F

Nov 1, 2018

The best in this series of courses so far. The maths was hard, and the programming assignments were accordingly at a higher level. But the applications of ConvNets are so fascinating, and their implications so profound, that I enjoyed every moment of this course.

By Pavan K V

Jan 19, 2018

the best course out of all 4 in deep learning.The best thing i liked most in this course is the applications such as

1) Image classification/Image recognition

2) Object detection-Automatic Car Driving

3) Face Verification and Face Recognition

4) Neural Style Transfer

By Zhao Y

Nov 25, 2017

This course gives me a deep understanding of CNN and also introduces me some latest information about face recognition. It makes me have an access to learn AI in an efficient way. Words seem to fail me when I want to show my gratitude to the teachers and mentors.

By Aparna G

Apr 24, 2022

It was a very interesting and application oriented course. The assignments were amazing. Got to learn so many concepts with hands on session. A big thank you to all the esteemed instructors, course designers and the unseen contributors of the coursera platform.

By Gautam K

Jul 8, 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 Chiew S ( L

Oct 9, 2022

From Face & Object Recognition to Self-Driving Cars

From Medical Imaging Diagnosis to Beautiful Arts Creation

Good combination of theory, wide range of real-life application, variety of hands-on programming assignments.

Insightful.  Impactful.  Fun

Great Course.

By C I

Dec 23, 2020

This was a really good course. Somewhat more challenging than the previous courses of this specialization. My favourite part of this course would probably be NST part in week 4. YOLO algorithm part was the hardest. But overall one of the best courses available.

By Alex 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.