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Вернуться к Convolutional Neural Networks

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

4.9
звезд
Оценки: 39,870
Рецензии: 5,270

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.

RS
11 дек. 2019 г.

Great Course Overall\n\nOne thing is that some videos are not edited properly so Andrew repeats the same thing, again and again, other than that great and simple explanation of such complicated tasks.

Фильтр по:

5026–5050 из 5,243 отзывов о курсе Convolutional Neural Networks

автор: Aditya K

16 апр. 2020 г.

The theory part is outstanding, concepts explanation is great but the programming assignments are not updated to TensorFlow 2.x that's an issue else everything was nice.

автор: Marco L S

10 дек. 2019 г.

I hoped there would have been a more theoretical explanation and also talks about why some nets are done in this way rather than another; it seems like it's all magic.

автор: Arjun V

18 мар. 2020 г.

Liked the concepts overall. The tieing up of basics concepts across different use cases could've been better explained from first principles and for better intuition.

автор: Amit A

2 сент. 2020 г.

Andrew Sir explanation is awesome, but please do explain concepts in videos also, as some programming assignments contain data, info that we are not having knowledge

автор: Sebastien M

1 авг. 2018 г.

I spend 1 week on the last assignment due of one bug. I am disappointed but the content of the course was good. Please next time react faster for correcting bugs

автор: Stanislav C

29 янв. 2018 г.

Grader in the last assignment is wrong. It has been reported in the discussion forums several months ago and still hasn't been. Apart from that, great content

автор: Jesus A F

20 янв. 2018 г.

The course gives you a good introduction to NN. However, the grading is buggy, and the content rather superficial. It gives you a false sense of achievement.

автор: Stefan M

14 июня 2019 г.

The homework assignments, compared to the other courses, where pretty low in quality. If these errors get corrected, I'd happily give this course 5/5 stars.

автор: Mathias E

25 окт. 2021 г.

V​ideos were mostly great!

Expected more of the written material (quizes, assignments, etc.), not the quality I would expect from something I've paid for...

автор: Uddhav D

7 июня 2019 г.

Some issues regarding the submission of assignments and some minute mistake in the videos and assignment. Although great teaching by Andrew as always :)

автор: Karol K

3 дек. 2017 г.

Issue with triplet loss function shouldn't happen. I had to remove "axis = -1" in order to pass grader even though function had produced wrong answer!!!

автор: Дмитрий Х

30 нояб. 2017 г.

There are a lot of issues with programming assignments grader (I've spent one hour to complete assignment and two days to make a grader to get it)

автор: Roel H

22 июня 2018 г.

The programming assignments contain bugs. Also the jupyter notebook kept on shutting down thus slowing down the learning process quite a bit :-(

автор: Kalana A

25 янв. 2019 г.

Certain Parts are not that much clear. Specially like in the triplet loss function, until the coding was done the real procedure was not clear.

автор: Kanishka D

27 дек. 2017 г.

the assignment setup and graders are not updated after reporting issues several times which caused a great deal of frustration among students.

автор: Félix P G

20 нояб. 2017 г.

The last exercise it was a litle annoyng, it took me almost five days to figure out how to solve the face recognition because a grader fault.

автор: Sergio B

13 дек. 2020 г.

I enjoyed the courses but I would like more practice, maybe a different module or examples aimed to help you define and optimize our models

автор: Serkan Ö

10 июня 2018 г.

There were repeats in the videos🤔 Also the answers to quizzes are not visible. If these would have existed, 5 stars would be reasonable.

автор: Rüveyda K

17 мар. 2018 г.

Sometimes it was very difficult to understand lecturer because of his accent, but apart from that, assignments and lessons were helpful

автор: Stephen D

17 мар. 2018 г.

This course is pretty good. Some things are not explained as well as Prof. Ng typically explains things, especially in the last week.

автор: Carol S

19 июля 2020 г.

The Neural Style Transfer notebook seems to have makes it difficult in the last panel to access the generated_image global variable.

автор: Jkernec

12 янв. 2018 г.

The assignments need to be reworked as they are quite confusing and the grading system is flawed especially for the last assignment.

автор: Jnana R D

13 мар. 2019 г.

More simple lectures with illustrations required and also graders need to fixed. Had a lot of time wasted because of buggy graders

автор: NEEL V

11 июня 2020 г.

It has very less explanation about working of back propagation of convolution network,

plus it can explain YOLO in much better way

автор: Aoun L

29 мая 2018 г.

The course is great but the assessments and grading is terrible, so many particularities and repetition that does not make sense.