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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:

4201 - Convolutional Neural Networks 的 4225 个评论(共 4,395 个)

创建者 Michael A

Jan 08, 2018

The programming exercises in week 4 have mistakes in them that have been reported over 2 months ago and still not fixed.

I would expect a payed course to exhibit a higher responsiveness.

创建者 Mario S

Jun 20, 2018

Content: good! state of the art!Lecture: to many cut mistakes of the videos such that many sentences are repeated.Exercises: content ok but notebook functionality and grader too buggy!

创建者 Bashyam A

Nov 25, 2017

The lectures were pretty good - however, the programming exercises were rather error-prone. Huge thanks to the Discussion Forum where other students had posted trouble-shooting tips.

创建者 Roya K

Dec 08, 2017

content was good,Yolo was hard and i still does not suggest,wasted too much time on exercises,when the answer was not match it passed! very bad experience with the exercise part.

创建者 Till R

Mar 07, 2019

Would have liked to learn more about why various architectural choices are made when building deep networks. The nitty-gritty details and Python exercises were a little boring.

创建者 Mostafa M

Aug 30, 2019

The last week (week 4) was not explained in enough detail. I was often frustrated because i was finding myself not fully understanding the concepts because of missing details.

创建者 Claire L

Mar 04, 2018

Content was great but the grading issues with the homework assignments made this course very time consuming and frustrating. Will recommend it when grading issues are fixed.

创建者 Aditya K

Apr 16, 2020

The theory part is outstanding, concepts explanation is great but the programming assignments are not updated to TensorFlow 2.x that's an issue else everything was nice.

创建者 Marco L S

Dec 10, 2019

I hoped there would have been a more theoretical explanation and also talks about why some nets are done in this way rather than another; it seems like it's all magic.

创建者 Arjun V

Mar 18, 2020

Liked the concepts overall. The tieing up of basics concepts across different use cases could've been better explained from first principles and for better intuition.

创建者 Sebastien M

Aug 01, 2018

I spend 1 week on the last assignment due of one bug. I am disappointed but the content of the course was good. Please next time react faster for correcting bugs

创建者 Stanislav C

Jan 29, 2018

Grader in the last assignment is wrong. It has been reported in the discussion forums several months ago and still hasn't been. Apart from that, great content

创建者 Jesus A F

Jan 20, 2018

The course gives you a good introduction to NN. However, the grading is buggy, and the content rather superficial. It gives you a false sense of achievement.

创建者 Stefan M

Jun 14, 2019

The homework assignments, compared to the other courses, where pretty low in quality. If these errors get corrected, I'd happily give this course 5/5 stars.

创建者 Uddhav D

Jun 07, 2019

Some issues regarding the submission of assignments and some minute mistake in the videos and assignment. Although great teaching by Andrew as always :)

创建者 Karol K

Dec 03, 2017

Issue with triplet loss function shouldn't happen. I had to remove "axis = -1" in order to pass grader even though function had produced wrong answer!!!

创建者 Dmitry

Nov 30, 2017

There are a lot of issues with programming assignments grader (I've spent one hour to complete assignment and two days to make a grader to get it)

创建者 Roel H

Jun 22, 2018

The programming assignments contain bugs. Also the jupyter notebook kept on shutting down thus slowing down the learning process quite a bit :-(

创建者 Kalana A

Jan 25, 2019

Certain Parts are not that much clear. Specially like in the triplet loss function, until the coding was done the real procedure was not clear.

创建者 Kanishka D

Dec 27, 2017

the assignment setup and graders are not updated after reporting issues several times which caused a great deal of frustration among students.

创建者 Felix P

Nov 20, 2017

The last exercise it was a litle annoyng, it took me almost five days to figure out how to solve the face recognition because a grader fault.

创建者 Serkan Ö

Jun 10, 2018

There were repeats in the videos🤔 Also the answers to quizzes are not visible. If these would have existed, 5 stars would be reasonable.

创建者 Rüveyda K

Mar 17, 2018

Sometimes it was very difficult to understand lecturer because of his accent, but apart from that, assignments and lessons were helpful

创建者 Stephen D

Mar 17, 2018

This course is pretty good. Some things are not explained as well as Prof. Ng typically explains things, especially in the last week.

创建者 Carol S

Jul 19, 2020

The Neural Style Transfer notebook seems to have makes it difficult in the last panel to access the generated_image global variable.