Chevron Left
Вернуться к Convolutional Neural Networks

Отзывы учащихся о курсе Convolutional Neural Networks от партнера deeplearning.ai

4.9
звезд
Оценки: 39,894
Рецензии: 5,275

О курсе

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....

Лучшие рецензии

AG
12 янв. 2019 г.

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.

RK
1 сент. 2019 г.

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.

Фильтр по:

5101–5125 из 5,245 отзывов о курсе Convolutional Neural Networks

автор: Kshitij S

15 окт. 2019 г.

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

автор: Himanshu A

23 авг. 2018 г.

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

автор: Adriano C

27 мар. 2020 г.

There are many things to improve in the programming assignment

автор: Dong Z

16 апр. 2020 г.

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

автор: Alex M

4 мар. 2020 г.

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

автор: Srijan G

4 янв. 2020 г.

The programming difficulty suddenly increased exponentially

автор: Michał Ł

12 мая 2018 г.

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

автор: Yiyun Z

16 янв. 2018 г.

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

автор: Jonathan B

25 нояб. 2019 г.

Good content but assignment grading has lots of problems!

автор: Andrea L G

4 февр. 2021 г.

Nice introduction. TensorFlow part can be improved a lot

автор: Shuo C

19 дек. 2020 г.

Great course but lots of bugs in assignments and videos.

автор: aman g

19 авг. 2020 г.

Programing assignments were more life fill in the blanks

автор: Xin H

11 нояб. 2019 г.

Some of the details are not very good just like yolo.

автор: André T D S

1 окт. 2018 г.

Bugs in the programming assignments kills the flow.

автор: STEFANO F P

1 окт. 2019 г.

Too easy excercises and with an old version of tf

автор: Fengjun W

17 дек. 2017 г.

I hate the errors in the assignments and graders

автор: Gleb F

9 янв. 2021 г.

Too much emphasis on python programming skills.

автор: Guglielmo F

31 дек. 2020 г.

The Neural Style Net sheet has to be reviewed!!

автор: Tze-Yuan C

30 апр. 2018 г.

The coding assignment is a little bit too brief

автор: Antoine H

7 дек. 2017 г.

Several bugs in the last programming assignment

автор: Maciej G

28 нояб. 2017 г.

too much material related to vision detection

автор: Han K K

6 янв. 2018 г.

Too much technical errors in the assignments

автор: lokesh w

3 февр. 2021 г.

n

e

e

d

m

o

r

e

o

f

m

a

s

i

n

g

a

n

d

p

o

s

e

d

e

t

e

c

t

i

o

n

t

e

c

h

n

i

q

u

e

s

автор: Chengqian W

31 июля 2018 г.

Some technical issues/errors in lectures.

автор: Patrick M

8 февр. 2019 г.

Too many mistakes in assignment material