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学生对 DeepLearning.AI 提供的 Convolutional Neural Networks 的评价和反馈

4.9
42,550 个评分

课程概述

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....

热门审阅

JM

Sep 19, 2020

Excellent, solid insights into working of models as well as providing references to the original work. THe assignments give practical examples of models one might want to implement for their own use.

AV

Jul 11, 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:

4826 - Convolutional Neural Networks 的 4850 个评论(共 5,641 个)

创建者 Hao Z

Dec 2, 2017

The bugs in the grading system make me uncomfortable. People have to submit the answer which is obviously wrong but favored by the grader to pass the test.

创建者 Hamlet B

Nov 19, 2017

The content was fun and very useful. The last programming assignment had some incorrect guidance and made the grading experience unnecessarily frustrating.

创建者 Jose-Luis L

Nov 26, 2019

The course is great. There is only one minor downside: sometimes the notebooks' connection is lost and you lose the latest modifications of your homework.

创建者 M J

Jul 2, 2019

A good introduction to CNN's if you haven't seen them before. Strong on concepts and motivations. Kinda vague on mathematical details and implementations.

创建者 preethi v

May 6, 2018

The course structure is really good. But please do fix the bugs in the assignments. Thanks to the discussion forum, it helped me a lot in fixing the bugs.

创建者 Sudipto C

Jan 1, 2018

Excellent content delivered very honestly by Prof. Andrew Ng. The course has some broken grader issues which need to be fixed to make this course awesome.

创建者 Jonatan K

Jan 6, 2020

explained very well

very interesting with andrew

the main problem with this course is bug fixing on assignments.. i lost alot of hours just because of this

创建者 Kenji M M

Sep 13, 2019

the last programming assingment has a lot of bugs as of 9/13/19 and was verry difficult to pass even though the actual code was very simple ti implement.

创建者 Yash R

Dec 24, 2021

It was a great course. Though the YOLO implementation part is a little confusing. Probably more implementation details could be covered in the lectures.

创建者 Ameya G

Dec 21, 2017

Course content was good and well structured. Some videos still need editing and grader for 2 assignments is faulty. Otherwise a very interesting course.

创建者 Nazmus S

Aug 4, 2019

ipython notebook fails often. It was a frustrating experience. There are many bugs to be fixed to run the homework problem submission process smoothly.

创建者 itay k

Dec 21, 2017

A great course! I would have gladly given it 5 stars, but currently, the assignment of week four have bugs and the notebooks tend to stuck or run slow.

创建者 Venkat K

Dec 5, 2017

A bit dense and fast-paced even for Prof Ng's usual standards - this course is drinking from a firehose, but a great hands-on introduction to ConvNets

创建者 Nitish S

Nov 7, 2019

Could have a better explanation of TensorFlow graphs in the assignments. The course is still very good and provides a solid conceptual understanding.

创建者 Frank H

Dec 17, 2017

Very interesting topics were covered in a quite comprehensive way. Only useful packages like Tensorflow and Keras were introduced only superficially.

创建者 E P

Nov 27, 2017

Another wonderful course by the team, even with a few bumps this is one of the best introductions to what the heck a convolutional neural network is!

创建者 Adithya J A

Aug 30, 2020

Great course and would totally recommend it. Assignments need a bit of work in terms of instruction clarity for use of certain tensor-flow commands.

创建者 Pablo M P

Aug 24, 2019

I learnt many interesting ideas about convolutional networks, however, the course needs to be checked by the staff. There are many bugs in the code!

创建者 Jarek D

May 19, 2018

Programming challenges in this course were less practical than in previous ones, and instructions sometimes a bit vague. Still recommend it, though.

创建者 Md R R J

Jun 25, 2020

The notebooks did not help much to practice skills received from video lectures. Specially last 2 weeks. Felt like translating formulas into codes.

创建者 Ernst H

Aug 4, 2019

Very good course. The assignments are too easy and I would be able to complete them without understanding the course material or what I am coding.

创建者 Nitish K

Apr 21, 2018

Neural Transfer and Object Identification (YOLO) was not explained very well. I had to look out for external videos on Yoututbe to understand YOLO.

创建者 Meriem S

Dec 3, 2017

CNN is not only used for image processing. It can be used in other fields. I hope so we can find other case study than image processing. thank you

创建者 Wu Y

Jan 7, 2019

Week 3 has a bad grading system for the programming assignment. The exact "0" blocked many time, and waste efforts. Otherwise, the course is good.

创建者 Jk L

Dec 17, 2017

It would be better if some gpus were provided, or the experiments of style transfer were a little painful. Anyway, the course itself is wonderful!