Chevron Left
返回到 Convolutional Neural Networks

學生對 deeplearning.ai 提供的 Convolutional Neural Networks 的評價和反饋

4.9
40,534 個評分
5,374 條評論

課程概述

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....

熱門審閱

OA

2020年9月3日

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.

RK

2019年9月1日

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.

篩選依據:

5001 - Convolutional Neural Networks 的 5025 個評論(共 5,348 個)

創建者 Steve d l C

2020年8月27日

good course

創建者 Sahil M

2020年5月5日

The Besttt.

創建者 Ankur G

2019年9月15日

informative

創建者 Sonia D

2019年1月30日

Very Useful

創建者 Luca M B

2018年8月1日

Quite nice.

創建者 Ayoub A I

2021年9月2日

Thank you!

創建者 Rishi J

2020年7月25日

Insightful

創建者 Yehang H

2018年1月2日

Some error

創建者 Mohamed A M

2020年10月5日

thank you

創建者 Yashwanth M

2019年7月16日

Very Good

創建者 Dave

2020年7月10日

good job

創建者 PRASANNA V R

2020年6月30日

Decent

創建者 CK P D

2020年3月31日

Thanks

創建者 Niranjan

2017年11月25日

Great

創建者 Hozoy

2022年2月22日

good

創建者 Sumera H

2020年9月13日

good

創建者 Isha J

2020年4月5日

good

創建者 Subhash A

2020年3月27日

good

創建者 VIGNESHKUMAR R

2019年10月24日

good

創建者 Rahila T

2018年10月8日

Good

創建者 Naveen K

2018年7月17日

good

創建者 Panchal S V

2018年6月28日

Good

創建者 CARLOS G G

2018年7月24日

g

創建者 Volodymyr M

2020年4月24日

This is not an education in any way. Yes, Convolutional Neural Networks provides good overview of convolutional networks and technology behind it. I like the way Andrew Ng structured material and his way to explain some details. Unfortunately, as a common problem for all "Deep Learning Specialization", theoretical material only scratches the surface of the knowledge. There is nothing deep in terms of theory. You will have to spend quite a lot of time digging for information yourself if you plan to use course material for any practical task, or assignment. In order to get missing pieces, I got to go through whole Spring 2017 CS231n. It is fine if you have enough time to see two sets of videos, but I expected to get same quality of material here, on Coursera.

Another course issue is quizzes. I am puzzled what these quizzes are testing. Provided answers often assume tentatively more than one correct variant. Probability theory works against you - you may happen to select correct answers for some questions , but definitely, not all of them. In the same time, it is quite easy to derive correct variant from second try.

Course programming assignments are complete disaster. While I kind liked programming assignments from week 1 and 2, I felt like I wasted my time working on programming assignments from week 3 and 4. I expected programming assignment to guide me through some training of complex networks, give some practical insight, which I can use for real-life tasks, but it was not there.

There is a good introduction to TensorFlow, while Keras is not even touched. And many assignments of week 3 and 4 are using Keras. It is necessary to peek-up theory and practice regarding Keras elsewhere. After one get enough knowledge about Keras elsewhere - guess what - programming assignment becomes useless as education, because it is too trivial.

I really wanted to rate this course as Two-Stars, but video materials and programming assignments from week 1 and week 2 slightly improved my attitude.

創建者 Yair S

2019年9月7日

While the online teaching of Prof. Ng, is excellent as in the other courses, this course specifically, has several pitfalls which can not be ignored:

1) The teaching and cover being given for TensorFlow are by far insufficient. If this subject is seen as an essential part of the course, it must be instructed systematically but this is not the case, unfortunately. More often than not, you find yourself doing guesswork in the assignments when it comes to TF code, which is also reflected in the Discussion Forum. So to summarize, TF must be covered in a systematic way, either in this course, or a previous one.

2) There is a bug on week 4 NST assignment, on the given code. Should be fixed.

3) There are several written correction to errors in OnLine videos. These Videos can and should be rerecorded.

4) Last but certainly not least: I have experienced frequent and really disturbing connection problems with the Python Notebook, with frequent connection errors, which can not be recovered and wherein one must open again the Notebook. While this was, to some extent, the case in other courses, in this course it was much more of a problem, especially in Week 4, probably due to a large amount of data, and where each rerun requires another 20 - 30 minutes. a MUST fix.

Thanks,

Y. Shachar.