Jul 12, 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
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.
by Harsh B•
Nov 06, 2017
This course is intended for ML learners who have background knowledge of NNs and want to enhance their scope of knowledge in CNNs. Prof. Andrew has been an amazing instructor. The material used in this course is mostly based on Tensorflow, so make sure to have a bit of prior knowledge in Tensorflow.
by พสิษฐ์ จ•
Apr 09, 2020
I have learnt a lot new things in this course, constructing exciting image/object detection projects with Tensorflow, Keras and even plain Numpy. Also, Andrew well explains many complex network architectures which illustrate various perspectives of the applications of convolutional neural networks.
by Vidar I•
Feb 13, 2018
This course really gets you started working with CNN. The only downside are the "bugs" in the assignments. My advise is to read the discussion forums before you do the assignment to know if there is a bug that you should know of before submitting.
Beside this minor bug, the course content is 5 star.
by Chitrao S R•
Jul 13, 2020
I liked everything about this course ! The instructor was very good at explaining the complex concepts and I really liked the quizzes and programming assignments , they really help brush up the concepts taught in the respective week !!! I would like to thank Andrew Ng for this amazing course !!!
by Damian C•
Mar 26, 2018
Really enjoyed learning more about the current state of the art of image recognition models. Although the structure needed can be at times overwhelming, the concepts are clear and implementation via open source packages make it feasible. Many thanks for making this available, keep the good work!
by Maciej F•
May 08, 2019
Somehow, a bit harder than rest of the courses for me. I had problems with tracking dimensionality and tensorflow notebooks were hard and difficult to debug. I think it would be nice if tensorflow has its own as a course or 2 weeks maybe. But anyway the concepts explanations is great as always!
by Juan M E B•
Apr 19, 2018
Excelent course. ConvNets are an eye-opening subject and the course explains the main concepts and applications in a simple way, indicating the source papers to understand better. I'd only ask for a couple of videos explaining in more detail backpropagation and the upload of the missing slides.
by Andrei N•
Sep 21, 2019
The content, examples, assignments, and quizzes are thoroughly developed. All the courses of the specialization share the same notation and lead a student from basic concepts to complex ones helping to develop an intuition on each step. The best course on topic of Deep Learning one could find.
by benedikt h•
Mar 10, 2018
great ! It is complex though, don't get fooled by the doable exercises - to really understand you can take several loops.
Imagine someone breaks up recent complex research paper into python notebooks for you and you get this delivered like a delicious food - this is how I feel about this class.
by Jun W•
Dec 16, 2017
This is an excellent course. Although I've got 100%, there are still some details and intuitions need to be figured out. Maybe I will go over it again. And of cause, I'm looking forward for the fifth course. I wish the fifth is not the last course. We still need to know reinforcement learning.
by Dr. R M•
Nov 07, 2017
Very informative lectures with simple explanations of what the algorithms are doing. The programming assignments are extremely detailed and well explained. This makes it very efficient and fun to learn the concepts of Conv Nets, Res Nets, the YOLO algorithm and so on in a short period of time.
by Jonathan M•
Jun 15, 2020
A great course overall. Ties together the concepts presented in the first 3 courses and does a great job of showing some very practical real life applications - the programming assignments show a wide range of practical applications of deep learning like face recognition, art generation, etc.
by Raul d A•
May 17, 2020
It was a great course. You end up with a pretty good understanding of convnets and their different applications and algorithms. For sure this course set up the basis for image processing work and research, although it is necessary to refresh concepts and go over the notebooks to fix concepts.
by Nour A•
Jan 07, 2019
The course explains topics I used to consider as "complicated" in a very clear and simple way. The videos and quizzes about theoretical concepts accompanied with programming assignments and extra reading material give solid understanding of the topic, its current trends, and future direction.
by Igor C C•
Nov 05, 2018
I think that should have an optional video with the mathematics behind the convolution/cross relation, showing element-wise operations on a small volume with more than one channel. I know most people will find it boring, but i think it will make easier to fully comprehend the 1x1 convolution.
by Wei F•
Dec 17, 2017
Really enjoyed learning this course. I'm a PhD Student in CS but neither in computer vision or NLP. I feel like these courses are sort of jump-starter, if you would like to learn more about DL and to be expert, there's a long way to go. However, this is really a good starter!! Thanks Andrew!
by Xinyu S•
Jul 15, 2020
I think this course offers enough technical details for me to understand how Conv Nets works. However, I find it much easier to undertand the contents if you take the Practice in TensorFlow first, where there is a more practical focus, and understand the big picture. Overall, great course!!
by Adarsh K•
Feb 04, 2020
The best place to start Computer Vision! You'll get to implement state of the art Techniques in CV, most with practical Application. The quizzes are very well designed and test your concepts. You'll learn to use open source implementations and build on top of that as well. Wonderful Course!
by Dipo D•
Jan 11, 2020
Like the other courses in the DeepLearing.ai certification, this course was also very crystal clear in teaching the concepts. Now, I can confidently read additional materials on Computer Vision. The assignments were also well thought out, kudos to all the TAs. Thanks for the awesome course.
by Rahuldeb D•
Sep 04, 2018
Another exceptional course offered by Coursera. There are lot of new concepts to learn in this course.
Prof. Andrew Ng has explained each and every concepts in very lucid manner. I want to give a big thanks to Andrew Ng and all other teaching associates for offering such a beautiful course.
by Brandon W•
Nov 24, 2017
Students had some technical issues throughout this course, with the autograder not correctly grading the assignments despite having all expected outputs correct. In time, I hope these issues can be fixed. However, given the level of instruction and quality of the course, still deserves a 5.
by Anoop P P•
Jun 10, 2020
The course has balanced of theoretical and practical aspects of Convolution neural network. Moreover, practical sessions encouraged to create a CNN from scratch, use a pre-trained model to fulfil the task. The assignments has helped to practice hands-on using tensorflow and Keras platform.
by Ajay S•
Aug 30, 2019
really a great course for the image learning . i love this course well . and thanks for providing me the financial aid for the course . this will really help me to complete my research work on time .
Thnaks. for the profession Andrew Ng . for the designing and teaching a wounderful course.
by HE Y•
Jun 24, 2020
I think this course offers an excellent illustration of convolutional neural network for beginners, even for those who have a basic knowledge about the neural network. The two applications of CNN are quite interesting and useful. I have learned a lot through this course and thanks Andrew!
by RUDRA P D•
Jun 20, 2020
Amzaing course on ConvNets but in my perspective anyone who wants to opt this course must have basic understanding how Tensorflow works and basic operations in it. Except every concept are well explained and also research papers are given (for who wants to dive deeper) in the assignments.