Chevron Left
Convolutional Neural Networks(으)로 돌아가기

deeplearning.ai의 Convolutional Neural Networks 학습자 리뷰 및 피드백

4.9
별점
39,719개의 평가
5,256개의 리뷰

강좌 소개

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....

최상위 리뷰

AR
2020년 7월 11일

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

AG
2019년 1월 12일

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.

필터링 기준:

Convolutional Neural Networks의 5,227개 리뷰 중 251~275

교육 기관: ANSHUMAN S

2019년 6월 4일

It has been a great journey through learning CNNs it was quite interesting rather than all other courses and I got to know really very new ideas which i can implement in my own models.

Once again I want to thanks Andrew Ng and all other teachers of Course

and a special thanks to Coursera for giving me this ample opportunity

교육 기관: Nick H

2019년 5월 22일

Awesome course if you want to understand the basics of CNNs along with recent applications of these algorithmns.

As usual, both Andrew's material and his presentation style kept me both engaged and interested to a point that I got ahead of the weekly schedule...which is probably a good metric in terms of course success

교육 기관: Nikhil V K

2019년 10월 20일

Great course by Andrew Ng sir. It gives us a great insight into many case of studies of state of the art ConvNet. Gives us a lot of intuition about object detection systems in autonomous driving and landmark detection , one shot learning for face recognition and a fun way of applying ConvNets for neural style transfer!

교육 기관: Wang F

2018년 1월 14일

Despite the confusing bug and server running problem in the last assignment of happy house ,

the course is still great . Compare to the other three ones, it's the hardest course for me by now .

You may feel stuck in some practice questions and program .Worth spending time to review the

stuffs of the course again。

교육 기관: Pawan S S

2021년 1월 8일

One of the best courses I found to learn convolutional neural networks as a beginner. All the subject matter are well structured and the flow of the module is very easy to follow and understand. Together with the programming assignments, I was able to quickly grab the essentials of CNN. I highly recommend this course.

교육 기관: Edson C

2020년 9월 3일

This was the most difficult course I did in this specialization, but I loved it, I loved it very much. Thank you very much dr. Andrew and coursera for the opportunity, I really understand the importance of studying computer vision and this course was very useful in this journey. Thank you very much, I really loved ...

교육 기관: 杨建文

2018년 1월 10일

The last 2 courses were delayed, but the positive side for me is that, in the beginning I proceed too fast and didn't learn that well, the delay made me take more time on such a valuable course, carefully reading and memorizing the instructions of assignments. I'm really grateful for Prof. Ng's excellent instructions.

교육 기관: Krishna M

2020년 6월 23일

This Course was exceptional and upto mark. I learnt a lot of stuff easily and was able to implement into the real world example. This was really helpful for building up my resume. I thank Andrew Ng and Coursera team for giving financial aid to take up this course. The amount of knowledge gained is so valuable to me.

교육 기관: Eric C

2019년 6월 23일

Awesome. This course was much more dense than the other ones, there is so many areas to review. Since this course is about my favorite subject, I will need to pause and rework on each individual points and associated papers (yolo, nst, similarity learning) which will probably take me weeks... Prof Andrew is the best

교육 기관: Arvind N

2017년 11월 2일

I thoroughly enjoyed taking this course. Beautifully designed...Thank you!

I had written a detailed review of the first 3 deeplearing.ai courses at : https://medium.com/towards-data-science/thoughts-after-taking-the-deeplearning-ai-courses-8568f132153

I will review this CNN course as well, in the form of a blog post.

교육 기관: Benjamín V A

2020년 7월 9일

Great course, provided many clear explanations I has been searching before. The one thing they could improve is that some of the practical exercises seem more focused in the framework than the algorithms. (I spent more time googling how to pass parameters to specific functions than actually using the algorithms)

교육 기관: Wade J

2018년 3월 25일

Good amount of challenge for after work learning. Nice exposure to different applications of AI. Fun.

Andrew Ng is awesome at explaining the concepts. Almost anybody would be able to understand them after he presents them. I also appreciate how genuine he is. You can trust that there is merit to what he tells you.

교육 기관: Glenn P

2017년 12월 10일

Another excellent course. Convolutional Neural Networks is no longer a mystery. I like the fact that Andrew doesn't teach this as an academic class but has a very practical approach that can be applied right way. He lets you know the strengths and weakness of each of the NN and gives his personal opinion as well.

교육 기관: Yijie

2018년 5월 16일

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.

교육 기관: Ahmad B E

2017년 11월 4일

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.

교육 기관: Yuri C

2021년 2월 10일

What a ride! I am not even very much into Deep Computer Vision, but this course made me finally understand how tensors algebra works and how they flow in the network. Andrew is just able to put it in so simple terms and in a very accessible way that just for that the course is already very remarkable! Congrats!

교육 기관: Parab N S

2019년 8월 25일

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.

교육 기관: Alejandro M

2019년 8월 5일

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.

교육 기관: Jeffrey T

2020년 3월 30일

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.

교육 기관: H A H

2020년 9월 12일

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...

교육 기관: Carlos A L P

2021년 1월 4일

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

교육 기관: MBOUOPDA M F

2020년 7월 16일

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.

교육 기관: Alexandre M

2019년 11월 29일

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.

교육 기관: Avineil J

2017년 12월 4일

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 :)

교육 기관: Samit H

2020년 8월 2일

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.