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Convolutional Neural Networks(으)로 돌아가기

deeplearning.ai의 Convolutional Neural Networks 학습자 리뷰 및 피드백

26,208개의 평가
3,161개의 리뷰

강좌 소개

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....

최상위 리뷰


Jan 13, 2019

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.


Sep 02, 2019

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.

필터링 기준:

Convolutional Neural Networks의 3,128개 리뷰 중 151~175

교육 기관: Mukund A

Feb 19, 2019

It was a really good experience. Best course available online. Well structured and well guided assignment. Got to learn a lot. Thank You!

교육 기관: Manpreet M

Feb 19, 2019

Splendid course with extremely useful content and exercises. After this course you will definitely be comfortable with CNNs.

교육 기관: 锐新华

Feb 19, 2019

very good course

교육 기관: Somex K G

Feb 20, 2019

this course help me to understand how ConvNet works and how can we implement it in various ways.

교육 기관: Qasid S

Feb 20, 2019

Great Course!!!

교육 기관: Sharath G

Feb 21, 2019

Made my concepts clear on Computervision.

교육 기관: Vidit G

Feb 22, 2019

very helpful

교육 기관: TanBui

Feb 23, 2019

Very good indication of CNN. However, some of the assignment materials such as Keras needs prior experience which are not presented in the course.

교육 기관: Xiao W

Feb 24, 2019

Very helpful and introductory

교육 기관: Beng C C

Feb 24, 2019

Excellent course!

교육 기관: Virginia

Feb 24, 2019

The course is a perfect balance between theoretical explanations, application in programming and tips that can be helpful if you intend to work with CNN. I had not seen CNN before, and I didn't feel lost at any moment. Every doubt I had was perfectly answered in the forum. You don't need much of an experience with TensorFlow or Keras to do the labs, which are accompanied by thorough explanations of what is required; on the other hand, there are "extra" tasks for people who want to go more into depth in each lab.

교육 기관: 林业雄

Feb 24, 2019

very good

교육 기관: Yan-Jen H

Feb 25, 2019

Nice course :)

교육 기관: 介阳阳

Mar 20, 2019

Excellent teaching! Not access to the assigment yet but already feel so excited!

교육 기관: LUCA D

Mar 21, 2019

Assignments are more challenging!

교육 기관: Khor H Q

Mar 21, 2019

very fundamental and guided well.

교육 기관: Vishnu N S

Mar 20, 2019

very good course and great content

교육 기관: Jimut B P

Mar 21, 2019


교육 기관: Akash G

Mar 20, 2019

The course was not in detail in terms of math and concepts. Like ML Course

교육 기관: Mahima m

Feb 27, 2019

Amazing course work with very good content.

교육 기관: Adam D

Feb 27, 2019

Andrew Ng explains thoroughly the state-of-the-art in object detection. Thank you!

교육 기관: Vikas K

Feb 27, 2019

thank you andrew for thing great knowledge sharing .

교육 기관: Reza

Mar 23, 2019

This course is easy to follow, cleared some black boxes for me. Even if you are not planning to purchase, it allows you to learn the most out of it by providing answered project assignment.

교육 기관: jason z

Mar 24, 2019

Very good topic.

Lesson 3 and lesson 4 can be improved or separate into new course with more depth.

교육 기관: Prajwal S N

Mar 24, 2019

Outstanding programming assignments. Well guided code. Concise lectures. Worth the time spent.