Chevron Left
返回到 Convolutional Neural Networks

学生对 deeplearning.ai 提供的 Convolutional Neural Networks 的评价和反馈

4.9
34,655 个评分
4,436 条评论

课程概述

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....

热门审阅

RS

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.

AR

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

筛选依据:

151 - Convolutional Neural Networks 的 175 个评论(共 4,397 个)

创建者 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!

创建者 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.

创建者 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.

创建者 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.

创建者 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.

创建者 Nelson F A

Aug 23, 2019

Excellent course with many hands on examples and filled with important resources on CNN architectures and other best practices. There are many optional reading material that I'm sure to come back too. The only thing missing was a little more insight on backpropagation on CNNs, although an example of it is given in a coding example. This is a course I will be coming back to for sure!

创建者 Ashutosh K

Nov 22, 2017

The best part about the course is the focus on understanding the basics. It takes time and effort to learn and follow through the lectures but once you understand the basics clearly, everything else becomes so much easy to understand. Not like some of the courses out there which push you into advanced coding from day 1 and then move backwards to basics, this course is so much better

创建者 Samuel Y

Dec 10, 2019

This course was awesome -- albeit pretty hard. I understood most of the concepts when learning them, but it was easy to forget a lot of the implementational details and such. Dr. Ng does such a good job, nevertheless, both presenting the material (which is straight out of cutting-edge papers) and also offering tips for actual implementation. I plan to make an app after this course.

创建者 Quentin G

Aug 09, 2018

Cours très intéressant et d'un niveau bien supérieur aux 3 modules précédents. J'ai vraiment du réfléchir sur de nombreux exercices de programmation pour arriver à mes fins. Merci beaucoup !

Very interesting courses. The difficulty level is very higher than the 3 previous courses. I really had to think everything twice on the programming assignments before submitting. Thanks a lot !

创建者 Rex F

Jan 30, 2018

i can't believe i learned so much, can read complex equations and translate them .. it's like a condensed math specialty mixed with learning real-world utilities and tools .. hey, i know from this course how to quickly and (almost) effortlessly prototype recurrent and other deep networks, how cool is that? because of this course i also became a contributor to Keras! yay for me :)

创建者 Roman V

Feb 24, 2020

I have become a great fun of deeplearning.ai and Andrew Ng. Thanks a lot of great high quality materials. Going through the specialization I'm falling in love with Deep Learning. I believe historically, deep learning, and especially ConvNets related papers are usually pretty hard to comprehend by simply reading them. This course made it so much more simpler, it is unbelievable.

创建者 Jamie K

Dec 23, 2019

Lots of new concepts in this course. I liked the literature review sections and the fact that Andrew starts to show you when it makes sense to pull someone else's model down and use that rather than building something from scratch. The programming exercises were also pretty good - I had to think in a number of places though they are still a little too structured for my liking.

创建者 Najeeb K

Aug 24, 2018

A great course providing in-depth theoretical understanding of Convolutional Neural Networks and state of the art model architectures for various Computer Vision tasks. I have been doing Machine Learning from past one and a half years but the course content still gave me wealth of knowledge in a structured format that I yearned for so long. Thanks Prof Andrew and the team! :)

创建者 Ajith

Jan 14, 2020

best course in world or unvierse to understand the basics and complex details of convolutional neural network .i would give an oscar for this course . I was so woried about the complex diagrams that i saw in internet about CNN but this course made it look very easy i was totally suprised how complex details were explained in simple manner .I would recommend this to everone .

创建者 Manjit P

Dec 07, 2017

This course covers lot more material and it is more application oriented compared to last three courses. I had to spend lot more time and effort for this one. Also, there are some bugs during submission of the assignments. There is enough discussion about those but I hope Coursera takes care of those in the near future. Nevertheless, I always enjoy Prof. Ng's lucid lectures.

创建者 Utkarsh M

May 19, 2020

This course was something different. Earlier when I started The Deep Learning Specialization, I was not interested in any particular application of Deep Learning, but this course gave developed interest in CNNs, so much so I'm seriously considering and planning to pursue my master's in Data Science. I wanna thank Andrew Ng for such great lectures, he has truly inspired me.

创建者 Yash M B

Jan 20, 2020

This course has given me everything that one can expect to learn from the field of Image processing models like CNNs, Deep Convolutional Models like Inception, VGG-16, VGG-19, ResNets, etc. Other topics were also learned that included me applying these concepts into real-world applications like the neural style transfer as well as the object detection and face recognition.

创建者 Marsh

Dec 02, 2017

The teaching style of Dr Ng is excellent as usual. He is able to take a complex topic and make it easy to understand. I found this course more challenging than the others in this specialization. It does require a bit of tenacity in order to finish the assignments. This is usual when coding. So don't give up and be sure to search the discussion forum when you hit a barrier.

创建者 Esteban C

Oct 08, 2019

Very good in-depth coverage of conv NN.

Just one little thing, week 4 Notebook assignments:

In style transfer code is not well explained how the train is actually working. In this case the input is set as a Variable instead of a Placeholder and this aspect is not mentioned or explained

In face recognition I still don't know how triple loss function is used during training

创建者 WALEED E

Mar 03, 2019

This course was the best I have ever taken. It gave me a big boost to carry my PhD research in robot vision with confidence of understanding what is happening all over the network and comprehension of one of the pioneer papers published in discussed in classes. Coding directly after finishing each week was the best to go to practice and apply all this knowledge gained.

创建者 ayush k

Apr 28, 2020

Quite lucid and good introduction to CNN for beginners to intermediate level. I specially liked the links and discussions about different papers along the course that Andrew recommends to read. For some who has just hear about CNN, but knows about basic NN, this is a really good course to learn main things super fast and then proceed into their own personal topics.

创建者 Kseniia P

Jun 30, 2019

Amazing course with clear explanations of how CNN works. Andrew gives you intuition and understanding of convolutions, pulling, padding, and explains the foundations in great detail, so you can understand state-of-art approaches and are ready to get hands on it. Thanks to the assignments' structure, you don't ever have to waste time on debugging irrelevant issues.

创建者 Teye

Apr 06, 2018

I love this course. I only wish there was an opportunity to go step by step from looking at images, creating the dataset from the images, creating labels, applying a model, and then testing. This would help to answer a few questions that I have. However, when I read the papers recommended, I assume many of those questions will be answered, such as : why max pool?

创建者 Umendra C

Jan 11, 2018

Best course on deep learning for computer vision! Convolutional networks can be tricky to understand, but Andrew has presented the material in a very easy to understand format. He starts with simple ideas and concepts and then build on them in an intuitive manner. Highly recommended course for anyone who wants to understand the deep convolutional neural networks.

创建者 Michal M

Feb 11, 2018

Excellent course. Time well spent.

Simple explanations of difficult concepts.

I was able to download yolo v2 in pytorch, reconfigure it to use CPU on my Mac, and get it running on my webcam in 1h after completing Week3 assignment.

Told all my friends how awesome the course is.

Keep up the fantastic work.

Super stoked for part 5!!! and learning GANs and RI afterwards.