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deeplearning.ai による Convolutional Neural Networks の受講者のレビューおよびフィードバック

4.9
36,570件の評価
4,742件のレビュー

コースについて

This course will teach you how to build convolutional neural networks and apply it to image data. Thanks to deep learning, computer vision is working far better than just two years ago, and this is enabling numerous exciting applications ranging from safe autonomous driving, to accurate face recognition, to automatic reading of radiology images. You will: - Understand how to build a convolutional neural network, including recent variations such as residual networks. - Know how to apply convolutional networks to visual detection and recognition tasks. - Know to use neural style transfer to generate art. - Be able to apply these algorithms to a variety of image, video, and other 2D or 3D data. This is the fourth course of the Deep Learning Specialization....

人気のレビュー

AG

Jan 13, 2019

Great course for kickoff into the world of CNN's. Gives a nice overview of existing architectures and certain applications of CNN's as well as giving some solid background in how they work internally.

RK

Sep 02, 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.

フィルター:

Convolutional Neural Networks: 351 - 375 / 4,692 レビュー

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 01, 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 Gautam K

Jul 08, 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 Oleksiy 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.

by Sayar B

Aug 16, 2018

Perhaps the toughest course so far, Convolutional Neural Networks introduces us to computer vision. Professor Andrew explains complex, state-of-the-art cases where computer vision is being used today. Great programming assignments, great lectures, great course.

by Shifeng X

Mar 25, 2018

awesome course! the assignment is actually not just a piece of homework, it indeed a kind of guidance, give you detail step by step examples of how to code the learned algorithm. Thanks to the lecturer, didn't find any course more 'user-friendly' than this one.

by Abel G

Nov 07, 2017

Wow.. what Can I say? This was the toughest of the three previous but super happy to be in this journey.

I learned a lot and I am motivated more than anytime to immerse myself in this field. There is so much to learn. Thanks to all the people behind this course!

by Ruby A

Aug 23, 2020

Excellent explanations of the theory and math behind the basics of CNN that anyone can understand easily. The assignments are also well designed in such a way that one could apply the theoretical knowledge gained to solve real time problems. Excellent course.

by Karthikeyan R

Dec 29, 2019

Again, excellent course from Andrew Ng! Made complex algorithms and concepts very clear! Got to know how CNN, Facial recognition and Object detection works. Reference to the literature paper will come handy in the future if one thought of diving deep into CNN.

by Julian S

Nov 20, 2017

Excellent course. Concepts very clearly described. Only improvement would be more Tensorflow and possibly Keras training. Yes, you can go elsewhere for this, but Andrew Ng is so good at explaining, I'd expect he'd do a better job!

Many thanks Mr Ng and team!!

by Reda M

Apr 07, 2020

Excellent course ! Theory and practice are covered in a relevant way, and Andrew's been very encouraging and clear all along this CNN journey ! The fun part is obviously art generation with the VGG19. Great thanks to Andrew and to the deeplearning.ai team !

by Yao F

May 20, 2019

The course is pretty good with advanced techniques on computer vision. The only regret is one problem about the last coding homework. I failed to load the pre-trained model and can only finish the home work without checking the accuracy of designed examples.

by Pankaj D

Dec 26, 2017

Amazing course plan and delivery! Classic CNN architectures, ResNet, YOLO, face-recognition, neural-transfers - all in a very succinct package! Some very minor issues with auto-grading of assignments, but nothing that the discussion forums won't get you thru.

by Ahammad U

Oct 18, 2020

Really great course in this deep learning specialization. I have enjoyed the entire course. Video quality is high and the instructor, Andrew is really awesome, I couldn't express in my word. Thank you Coursera for giving me the chance to complete the course.

by Jayaram R

Jan 28, 2019

Andrew's explanations, and the exercises are absolutely fantastic. There seems to be a lot of tricky math in Convolution Neural Networks and Andrew's explanations and illustrations help students understand the essential concepts behind each type of Conv net.

by Paul S

Nov 29, 2018

Excellent course. Very good and well structured explanations by Andrew Ng: one concept per video, sometimes a second video to explain why the concept works or to give some intuition. Course covers many of the classis deep learning papers. Highly recommended.

by Joshua P J

Aug 07, 2018

Weeks 1 & 2 were very good. Week 4 was excellent with extremely clear presentation. I didn't like week 3; it felt like the topics were presented in random order, and the homework felt trivial (I finished it easily but I still have no idea what was going on).

by Camila B V

Mar 25, 2020

Awesome, I loved taking this course, the way to explain the topics is the best. I enjoyed every part of this course and the most important part I understanded several concepts. The exercises and material class are really usefull. Congrats you're the best.

by Kaan A

Jul 30, 2019

This course was the greatest one among the first 4 courses of the Deep Learning Specialization. Real world examples were perfect. Moreover, the paper suggestions helped me a lot to learn through my process of this course. Thank you Andrew and Coursera Team.

by Michael G

Nov 16, 2018

Great examples and walkthroughs. I didn't think I would be able to code all the various CNN architectures, but this course made that process challenging, but doable. Now it is time to start working on side projects to sharpen the skills I have learned here.

by Artem P

Apr 22, 2018

Probably the best course in the specialization (well, along with Sequence models). 50 layer VGG model built in Keras gives awesome enterprise-level results on a relatively small data sets..! But I recommend taking all these courses, they are all very good.