Dec 12, 2019
Great Course Overall\n\nOne thing is that some videos are not edited properly so Andrew repeats the same thing, again and again, other than that great and simple explanation of such complicated tasks.
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.
by Yuwen W•
Apr 01, 2020
De-mystified sophisticated topics as always. Thru this course, I get a good understanding of the concept and basic building blocks of CNN, and the idea behind object localization, face recognition, neural style transfer.
After this course, I feel there is still a big gap between understanding the concepts and using them in the real world. Will move on to the tensorflow specialization to get more hands-on practice.
by Mohd Z C A•
Jan 18, 2020
The lectures, quizzes and assignments are designed to help you to understand the topics, not to penalize you. Real-life applications really help me to understand the concepts and the underlying principles. Only one minor issue that I think needs to be addressed - the use of older version of TensorFlow. The latest TensorFlow is not backward compatible and causes major issue when I tried to run the codes locally.
by ANTHONY R•
Nov 12, 2019
Excellent course with sufficient detail to become instantaneously productive, but at same time more deeper appreciation of internals that must be mastered when beginning designs don't work. Good launch point for learning new DNNs that are part of open source. Much better than Tensor Flow courses that just want you to know how to use the tool. I am ready to tackle my application which is wireless communications.
by Leigh L•
Dec 14, 2018
This course is a wonderful journey for me. I can certainly apply CNN skills into some of very interesting fields. I have already begun to experience other styles to argument my son's photo. It is a great fun. The facial recognition technique is great to learn. I'm living in China now. Chinese government applies the FR into many public CCTV. It is interesting to observe how they are using it (to say the least :)
by Melvin M•
Sep 02, 2019
An incredible course about "Convolutional Neural Networks" and related applications to image data. A complete and in-depth course concerning the most important concepts and algorithms about Computer Vision. Furthermore, a fun implementation section which enables youto to create exciting applications ranging from safe autonomous driving, to accurate face recognition, to automatic reading of radiology images.
by Akshay N•
Oct 22, 2018
Very well structured and informative course. Got to learn plenty of new things, as well as an intuitive understanding of ubiquitous applications like face recognition. The only downside is that for learners not having a hold of frameworks like Tensorflow, the assignments can be a little challenging to tackle. Nonetheless, it helped me glean a very comprehensive understanding of CNNs. Keep up the good work.
by Pui L H (•
May 02, 2018
This is a great series of courses. He made things really clear and easy to understand. The assignments examples are so clear and neat. I actually used many assignments as a building block of my machine learning projects in production. I really hope that Dr Andrew Ng will give another series of courses about machine learning again, especially in the reinforcement learning area and the latest technology.
by Qiongxue S•
Mar 04, 2019
I learned a lot from this CNN course, notations, algorithms, tensorflow and keras application. I would strongly recommand to learn this course. It made me think a lot smart applications in daily life and know better about what artifical intelligence is. Of course this is far more than enough, and I will keep learning the related knowledge and reading more about NN. Thanks a lot for the excellent tutorial!
by Rohit K•
Jul 06, 2019
Hello Andrew, I am a big fan of you. Learning from your every course. Very unfortunate that I can do that remotely only.
One thing that I want to mention - Can we have lecture notes on coursera, just like the way used to in CS229 that we can read before coming to next lecture. I found that that was very useful in understanding when things get harder.
Thanks hope we can improve coursera in that matter.
by Kocić O•
Mar 15, 2018
This course is almost perfect. It gives all the intuition that one might need about ConvNets and it introduces you to the most exciting papers in the field gently and in a fun way. However, in my personal opinion backpropagation of ConvNets should be treated in more details even if that requires some mathematical rigor. One more argument to this is that it can always be made an optional video/assignment.
by Atul A•
Dec 12, 2017
Excellent course! One of the best courses on ConvNet; it is rigorous and yet fun because of the broad range of projects - from Object Detection to Face Recognition / Face Verification and Neural Style Transfer. Andrew Ng's hallmark is his rigorous and thorough instructions from first principles. I would highly recommend this course to anyone looking to dive deeper into deep learning and computer vision!
by ANGIRA S•
Mar 31, 2018
This can be like the journey where you start as an acquaintance to the CNN's and end as an intimate friend. The excellent thing about this particular course is that it'll introduce you to the seminal computer vision papers and Prof. Ng will also guide as to the difficulty level of the papers. Another amazing learning opportunity is the case study. The text is already online, but the learning is here!
by Vitalija S•
Jun 30, 2020
Loved it but just as others have noted, programming exercises could have more comments about what we are doing because I had to spend lots of time trying to figure out what the task wants me to do. In addition, many links provided in comments about tensorflow documentation don't work. But as I said, this course was amazing because it helped me to understand many important things about CNN. Thank you.
by Rahul M•
Feb 14, 2018
This is just exceptional. Making cutting edge research accessible to learners. Making tough concepts available and understandable to beginner/intermediate students is hard enough, but Andrew makes it look easy. Some optional assignments where learners do everything from scratch would be good preparation for the real world - maybe this can be part of a capstone added at the end of this specialization.
by Bo M•
Jan 08, 2018
Some teach so that you understand that they understand. Others teach so that you understand. Andrew Ng belongs to the latter category. The course presents detailed overview of convolutional neural network with concepts ranging from 1D, 2D and 3D convolution, through max and average pooling, to style transfer. All concepts are carefully explained, with great illustrations and easy to follow examples.
by Apperson H J•
Jul 12, 2020
Course was great (as expected, Andrew is a terrific lecturer) - but it has a couple of problems:
* There are several errors that are pointed out, but sould be fixed in the lecture
* The exercises should use a more recent (ideally current) version of tensorflow
* You need to provide a utility that allows students to download ALL of the material involved (even imagedata that is accessible by links)
May 07, 2020
this course taught me the intuition and application Convolutional Neural Networks in the field of computer vision , Face recognition, face verification and Neural style transfer. I am very much intrigued to learn apply face recognition model into my project this helped me to understand papers and the explanation of Andrew is wonderful the advises he give really helps use while building projects.
by Travis J•
May 28, 2018
This was a very decent exploration of how Convolutional Neural Networks are used to solve various computer vision problems. The one complaint I have is that I wish the course wouldn't assume so much familiarity with Tensorflow and Keras frameworks in the assignments. The brief exposure to these frameworks earlier in the coursework is hardly sufficient to prepare one for the later assignments.
by Ivan S•
Feb 24, 2018
Great course, the best CNN explanations I've seen so far on the internet. After finishing the course I have much more deeper understanding of convolutions. It is very helpful that we must code convolution neural network by hands with numpy as it greatly helps to understand the problem. The state-of-the-art examples are very interesting and helpful also. Loved to see Keras and tensorflow here.
by Zhixun H•
Feb 23, 2018
Definitely 5+ stars. You got some much precious experience to implement those start-of-the-art deep learning applications with so much detailed explanation, supportive peer learners. It's really impossible for anywhere else to provide you this package to learn CNN, INN, YOLO, NST, FaceNet and so on so forth. I'm so grateful for the heart the teaching team pours into this course. Thank you.
by Lucas G•
Nov 05, 2017
As in all the previous courses in this specializations, Andrew Ng teaches the basics of neural networks in a clear, easy to understand manner. The programming exercises give nice hands-on examples of how you can apply the models described in the lecture, teaching both how to program the algorithms from scratch, and how to use higher level packages like keras and tensorflow. Great course!
by Brandon K•
Nov 19, 2017
This was my favorite class of the specialization so far. We've finally built up to the point where we can do some of the sexy things deep learning is known for. I have to say, I'm getting sick of having to submit every assignment 2 or 3 times and waiting for up to 2 hours to see if I passed because the Coursera grader doesn't want to work properly, but that isn't the instructor's fault.
by Victor A M B•
Apr 07, 2020
Es un curso que te enseña los fundamentos, técnicas y variaciones de las CovNets (Redes Neuronales con Convoluciones). Este curso es bastante bueno para introducirse en el mundo del análisis de imágenes y otros campos que utilicen datos no estructurados. Muy recomendado el curso, pero vean primeros los otros cursos de esta especialización para que pueden entender mejor los conceptos.
by Jason J D•
Aug 18, 2019
Another wonderful course in this specialization. The course covers many important topics in the field of Deep Learning such as CNN architecture and models, ResNets, Object Detection, Face Recognition, Neural Style Transfer and even a tutorial on the popular DL library Keras. The programming exercises and fun to complete and the course content is top-notch as always from Prof. Andrew.
by Sriram V•
Oct 17, 2019
Programming exercises need to made really with right structure as the YOLO one was very poor. Problems are very easy and makes this course very simple. We need to incorporate right amount of programming along with concepts, make it tough and train us also really well in the ideas. Concepts are absolutely fine, it takes the slow pace to make us understand deeper ideas and intuitions.