Great course. Easy to understand and with very synthetized information on the most relevant topics, even though some videos repeat information due to wrong edition, everything is still understandable.
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.
It is a great course that covers most part of Convolutional Neural Networks. I have learned a lot from it. Thanks Andrew! Only one suggestion: we have learned dropout and the batch norm in previous courses. Because they are such important tricks, it would be better if you could cover how they can be used in CNN.
by Ahmad B E•
Greatest cores for me till now on deep learning. I recommend it for deep learner or computer vision student. The best thing in this course is that it is very practical and up to date, and full of research papers of algorithms that Google and Facebook currently uses. Thanks a lot Prof Andrew Ng you are the best.
by Parab N S•
An Excellent Course to make people understand Convolutional Neural Networks in good depth and with ease. The detailed understanding of the major Convolutional models like YOLO and ResNet is like an icing on the cake. I would like to thank Professor Andrew N.G. and his team for developing this wonderful course.
by Alejandro M v G•
Muy bueno para empezar a entender los conceptos de las capas convolucionales. Luego muestra modelos profundos como AlexNet, VGG16, ResNET, Inception que se pueden entrenar usando transfer learning. La parte de detección de objetos es la mas complicada. La parte que más me gusto fue la de reconocimiento facial.
by Jeffrey T•
The intuition and examples made this course easy to understand and learn. I loved how Andrew decomposed current published papers into an easy to understand format. All of the important points to remember were highlighted without wasting time on the minutia. Thanks for all the hard work put into the course.
by H A H•
I enjoyed a lot in this course...who wants to know how to build the CNN model...then this course is absolutely for them..they should try 100% this course. this course gives u insights into how to build your CNN model this one is I think the best course for that...thank u sir for this type of good content...
by Carlos A L P•
Nice exploration of CNN theory covering theory and Python exercises through different algorithms. One recommendation would be update broken links and re-write comments in code as sometimes it is not clear what variable or what is needed to complete the required functionality, specially on ungraded exercises
by MBOUOPDA M F•
This course explains the details of CNNs with a great simplicity. It also presents some state of the art CNN architectures with their ideas very clearly. Finally the assignments allow to implement several CNNs and also show how transfer learning is used to perform face recognition and neural style transfer.
by Alex M•
One of the most important courses in the Deep Learning Specialization in my opinion. Good content, enjoyed the homework, lots of details for beginners and extra resources for more advance content. Would definitely recommend for anyone interested in working in Machine Learning especially in Computer Vision.
by Avineil J•
Exceptional Course. Learnt a lot from it. Takes a different approach to teaching than other courses in the sense that more focus is on applications rather than training of models for which a GPU cluster is a must. Thanks Andrew Ng and his team for the wonderful course. Looking forward to sequence models :)
by Samit H•
This is the course I enjoyed the most among the Deep Learning Specialization Course threads. Seems very practical to me and I learned a lot about CNN. A few more detailed practice in notebook problems could've made things more interesting. Many thanks to Andrew Ng for making such wonderful lecture videos.
by OMAL P B•
An amazing course to get an advance knowlege and practise "Convolutional Neural Networks". Andrew Sir makes the math and concepts behind the scenes very easy to understand. The course is easy to follow as it gradually moves from the basics to more advanced topics, building gradually.
by Jizhou Y•
Professor Andrew is really knowledgeable. The lecture videos he makes are really helpful for me. I really learn a lot from them. Also, the recommended learning materials such as academic paper he recommend are really useful for me if I want to further my learning on the residual network or YOLO algorithm.
by J.-F. R•
Great course by Prof Ng. I had taken his Machine Learning course a few years ago, so expected high standards of content and assignment preparation - I was not disappointed. Staff is very responsive and helpful in forums as well. I highly recommend it. Taken as part of the DeepLearning specialization.
by George Z•
Exceptional course taking you into the real world of deep learning by exploring new concepts and classical architectures like LeNet-5, AlexNet, VGG-16, ResNet, R-CNN, YOLO, FaceNet and Style Transfer that propelled deep learning in new heights. Loved every part of it (minus some hiccups with the grader).
by Mukesh K•
The course is just awesome both in terms of content that is being taught in the lectures and the assignments. Though, I think the last week is not that much important for the industry purpose but definitely it is good for those who are interested in non-industrial use of tensor flow and neural networks.
by Yong B S•
it's a wonderful course to learn CNN. thanks to the Prof. Ng for his excellent teaching. the programming assignment is clearly explained and structured. it is easy for student to follow and understand what they are doing. I am really enjoyed the learning. again, thank you very much Prof. Andrew Ng !!!
by Ignacio H M•
I finally understand YOLO! This course has the best material available on CNNs. Even though I come from a MSc in Computer Vision and Machine Learning, we didn't have enough time to fully cover 'complex' architectures such as YOLO. Thanks to this course I feel more up to date in the Deep Learning field.
by Victor F d P•
Once more Andrew steps up as a brilliant teacher. I'm a biologist looking to improve my data science skills to better tackle medical imaging problems. I'm confident to say Andrew is the reason I'm going to make a difference in low resource communities in the future. Thank you, Andrew, you are awesome.
by Scott H•
I really enjoyed this course. I found it pretty approachable. FWIW, I'd taken Andrew's original ML class, but then skipped 1,2, and 3 of the new one (and jumped into 4) The course really holds your hand, so be prepared to force yourself to try some of this on your own to be sure you've understood it.
by Harsh B•
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 Kevin C•
El mejor curso hasta ahora (me falta el de RNN). Los temas son bastante interesantes y sus aplicaciones hacen que el curso sea muy bueno, tanto en los cuestionarios como en los ejercicios de programación. Quizás sea necesario el feedback en los cuestionarios para saber por qué algo está bien o mal.
by พสิษฐ์ จ•
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•
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 Pranab S•
I am loving the journey I have started with DeepLearning.AI .Thank you to the amazing Teacher Andrew Ng. Sir for offering such wonderful online course which is affordable to anyone anywhere in this world. Thank you so much and I am looking forward to finish the last course of this specialization.