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Convolutional Neural Networks に戻る による Convolutional Neural Networks の受講者のレビューおよびフィードバック



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....



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.


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.


Convolutional Neural Networks: 5026 - 5050 / 5,198 レビュー

by Carsten F


The course was good but waiting for the 5th part of the 5-part specialization for months is a pain.

by der b


Going from lecture to code is too sparse. Needs sample or pseudo-code that can be used as a guide.

by Kyusun J


Every Course is in youtube. Don't know why i paid for this. The programming exercises are oudated.

by Dylan R


Lecture editing and programming assignment quality start to go seriously downhill in this course.

by Alex H


The course is not ready for prime time: grader and exercise errors would make people bald. :)

by Håvard S


Lectures are brilliant - but the course is let down by issues with the programming exercises.

by Nagaraj R


Object detection chapter was too overwhelming and I wish Mr. Ng had dumbed it down a shade.

by Renato R d S


It will be very important an update, especially at week 1. A lot of commands are not used.

by Simeon S


Good overview over the materials, but there are a lot of clipping errors and typo's....

by Mohamed E


Needs to discuss more applications outside of image classification and computer vision.

by Chenming X


It is hard to understand the code and the training is limited in the coding homework.

by rudy F


course was good but server/grader bugs in the programming tests were demotivating...

by Paul H C


Really interesting from a theoritical standpoint but the exercise are too guided..

by Alan P


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

by Tom B


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

by Maysa M G d M


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

by Ishan B


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

by Hair P


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

by Xiaohua Z


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

by Shabnam M V


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

by Alec G


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

by Samuel C


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

by Nele V S


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

by Shivanand P


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

by James W


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