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Convolutional Neural Networks(으)로 돌아가기

deeplearning.ai의 Convolutional Neural Networks 학습자 리뷰 및 피드백

40,630개의 평가

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


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


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 5,361개 리뷰 중 5201~5225

교육 기관: Alan P

2017년 12월 9일

Too much bugs in program assignment and sometimes the instructions are not clear!!

교육 기관: Tom B

2018년 7월 24일

programming assignments are of lower quality than previous sections of the course

교육 기관: Maysa M G d M

2018년 4월 28일

I would like to see the implementation from scratch, not only pre-trained things.

교육 기관: Ishan B

2018년 1월 18일

There were issues with the Coding Assignments. Lots of inconsistencies in grading

교육 기관: Hair P

2020년 6월 24일

This course is great, but it DEFINITELY needs to be updated to Tensorflow 2.0

교육 기관: Xiaohua Z

2018년 6월 11일

Terrible grading system waste u tons of time.The content itself is excellent.

교육 기관: Shabnam M V

2020년 7월 31일

The explanations of the first 3 courses were better and easier to understand

교육 기관: Alec G

2019년 3월 2일

The grader was frustrating on the programming assignments, especially week 4

교육 기관: Samuel C

2017년 11월 26일

Class itself is great, but the buggy grader software should be fixed timely

교육 기관: Nele V S

2021년 1월 4일

a pity that part of the keras code in the practical exercises is outdated

교육 기관: Shivanand P

2019년 3월 2일

Grading process/grader need to be improved for Week 3 and 4 assiignments

교육 기관: James W

2019년 2월 13일

Some of the coding assignments had major issues that need to be fixed.

교육 기관: 김윤수

2018년 5월 14일

need to teach us more about tensorflow to do last week's assignments

교육 기관: Alex K

2019년 6월 7일

Good content but the Coursera homework platform is severely broken.

교육 기관: Iván I

2019년 10월 26일

The videos are not properly edited. Exercises are not very useful.

교육 기관: Kshitij S

2019년 10월 15일

A bit difficult than prior courses. Still, enjoyed learning. :)

교육 기관: Himanshu A

2018년 8월 23일

The convolution operator seemed a bit abrupt in the first week.

교육 기관: Adriano C

2020년 3월 27일

There are many things to improve in the programming assignment

교육 기관: Dong Z

2020년 4월 16일

Not very clear, still need to learn a lot to understand CNN.

교육 기관: Alex M

2020년 3월 4일

The FaceNet assignment is bugged as hell! Please fix it ASAP

교육 기관: Srijan G

2020년 1월 4일

The programming difficulty suddenly increased exponentially

교육 기관: Michał Ł

2018년 5월 12일

Very nice course, but grader issues kill all the pleasure.

교육 기관: Yiyun Z

2018년 1월 16일

The the Yolo assignment, the IOU part has grading problem!

교육 기관: Jonathan B

2019년 11월 25일

Good content but assignment grading has lots of problems!

교육 기관: Andrea L G

2021년 2월 4일

Nice introduction. TensorFlow part can be improved a lot