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Отзывы учащихся о курсе Convolutional Neural Networks от партнера

Оценки: 40,520
Рецензии: 5,372

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


3 сент. 2020 г.

Great course. Easy to understand and with very synthetized information on the most relevant topics, even though some videos repeat information due to wrong edition, everything is still understandable.


11 июля 2020 г.

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

Фильтр по:

4801–4825 из 5,347 отзывов о курсе Convolutional Neural Networks

автор: Xiaojie H

25 мар. 2018 г.

More Tensorflow related introductions in the program assignments are needed.

автор: Yevgeniy D

18 нояб. 2017 г.

The course is good, but the grader is something that makes your hair go grey

автор: Abrar H

28 мая 2020 г.

The course content is very good. but I think assignments need to be harder.

автор: Vysakh R

27 сент. 2020 г.

It was tough. Tensorflow knowledge is a must prerequisite for this course.

автор: Narayanan S

15 мар. 2019 г.

Very good introduction. I wish the assignments were a bit more challenging

автор: Alex N

27 дек. 2017 г.

Please fix the grader in Week 4 - Face recognition - Triplet loss exercise

автор: Pierrick R

27 февр. 2021 г.

I think that the exercices are really easy, you have to change this part.

автор: Ahouba C A A

24 июня 2020 г.

I wish there had been more explanations something regarding propagations.

автор: Kalyan A

2 мая 2020 г.

one less star because you are not giving me any material for this course.

автор: MEKALA S N

1 мая 2020 г.

Overall course was good. Some videos are lengthy, people might get bored.

автор: Christian A

26 февр. 2019 г.

excellent course. the jupyter notebooks were behaving erratically though.

автор: Amit K

14 апр. 2018 г.

this one was hard to clear thanks for wonder full tutorials and questions

автор: Fereydoon V

26 февр. 2018 г.

Tensorflow and Keras tutorials need improvement and further explanations.

автор: Benjamin H D

11 дек. 2017 г.

Material is great as always, the audio could certainly be improved though

автор: Katharina E

9 янв. 2021 г.

Content is great, but the auto grader has issues costing a lot of time!

автор: Michael F

24 мая 2018 г.

Programming assignments are too easy, consisting largely of copy&paste.

автор: Richard Y

25 февр. 2018 г.

Very good course. Just please fix the buggggggggy grader in the week 3.

автор: Pengbo L

24 янв. 2018 г.

The last assignment on triple-loss has the grader-error, which a couple

автор: Dino P

2 июля 2020 г.

I'd have given it 5 if programming exercises were modified to use TF2.

автор: Ukachi O

10 мая 2020 г.

A wonderful introduction and implementation to the concepts of CovNets

автор: Vamvakaris M

8 сент. 2019 г.

It required coding on keras and tensorflow not appropriete introduced.

автор: Emmanuel R

10 июня 2018 г.

Very hard at week 2. Week 3 and Week 4 were very exciting. I liked it.

автор: Clay R

21 февр. 2018 г.

The grader could use some more debugging but otherwise excellent work.

автор: David P

6 дек. 2017 г.

Great course! Assignment notebooks could be a bit more challenging...

автор: Rafael G M

26 янв. 2020 г.

Good material.

I recommend explaining YOLO with more conceptual depth