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Вернуться к Convolutional Neural Networks

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

4.9
звезд
Оценки: 39,866
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

AR
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

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:

5001–5025 из 5,241 отзывов о курсе Convolutional Neural Networks

автор: Lavínia M T

26 нояб. 2020 г.

The Face Recognition lab just don't make any sense, the expected outputs are the ones in the Face Recognition for the Happy House. And it made the exercise very annoying! Despite it, the course is really good.

автор: Denys G

3 дек. 2017 г.

The production of the course felt rushed, there are numerous clipping issues in the videos and a major bug in one of the assignments. Also, for such a key topic to be covered in only 4 weeks felt very shallow.

автор: E S

21 янв. 2018 г.

Good explanations of the material but bugs in homework assignments and better explanations of tf usages is required for certain assignments. A refresher of tf via an additional assignment would've been nice.

автор: Daniel M

27 янв. 2018 г.

Good insights on the YOLO algorithm as well as in Siamese networks and triplet loss. Miss some more deeper understanding both in the lectures and the assignments, but I totally recommend the course anyway.

автор: ashwin m

22 июля 2019 г.

very good topics discussed ,facial recognition and facial verification assignments do not do justice to the complexity involved.practical knowledge gained is less compared to other modules prior to this.

автор: Carlos V

16 июля 2020 г.

The knowledge is good, and the techniques taught are valuable; however, having to use a deprecated version of TensorFlow is annoying and a lot of this will have to be re-learned to be put into practice.

автор: Hagay G

26 апр. 2019 г.

Course is very informative.

Unfortunately, unlike other courses in the spec, there were quite a few bugs in the notebooks and they took quite a while to load due to the sheer weight of the models loaded.

автор: David v L

2 янв. 2018 г.

Face recognition is a bit oversimplified, there is more to it that a simple accuracy metric. Priors are involved, which are included in the NN training, but should really be disassociated in evaluation.

автор: João G V

23 янв. 2020 г.

In contrast to course 1 and 2, I've found the videos to be rather shallow (no pun intended), in the sense that, in my opinion, they haven't explained thoroughly the techniques' underlying mathematics.

автор: Ramon S

20 июня 2021 г.

The information in the lectures was brilliant. However, the coding assignments don't really test your understanding of the course, rather your ability to piece together the authors previous code.

автор: Joscha O

3 янв. 2018 г.

This is a very interesting and well structured but the assignments in week 4 got alot of bugs, grading gives zero points for the right ouput (according to the notebook) and ten for a wrong one...

автор: Swaraj L

4 апр. 2020 г.

The course starts normal but suddenly gets very confusing from the start of week 2. Also it gets a bit difficult to understand things later on. Otherwise its very good course and i enjoyed it

автор: Marcela H B

27 авг. 2021 г.

Overall the specialization this course is the more complex, not only regarding the main concepts I think that the assignments are hard and will be usefull have more context about tensorflow

автор: Martin S

16 мая 2021 г.

So far I was very enthusiastic about the courses but this one is rather disappointing. Unfortunately, the video editing is very poor, if done at all, which make listening somewhat annoying.

автор: George C

15 янв. 2018 г.

Some frustrating issues with the week 4 assignments. I would also like some explanation on how to download all the related materials so I can play with the models later on my own machine.

автор: Michael A

8 янв. 2018 г.

The programming exercises in week 4 have mistakes in them that have been reported over 2 months ago and still not fixed.

I would expect a payed course to exhibit a higher responsiveness.

автор: Mario S

20 июня 2018 г.

Content: good! state of the art!Lecture: to many cut mistakes of the videos such that many sentences are repeated.Exercises: content ok but notebook functionality and grader too buggy!

автор: Bashyam A

25 нояб. 2017 г.

The lectures were pretty good - however, the programming exercises were rather error-prone. Huge thanks to the Discussion Forum where other students had posted trouble-shooting tips.

автор: Roya K

8 дек. 2017 г.

content was good,Yolo was hard and i still does not suggest,wasted too much time on exercises,when the answer was not match it passed! very bad experience with the exercise part.

автор: Till R

6 мар. 2019 г.

Would have liked to learn more about why various architectural choices are made when building deep networks. The nitty-gritty details and Python exercises were a little boring.

автор: Mostafa M

30 авг. 2019 г.

The last week (week 4) was not explained in enough detail. I was often frustrated because i was finding myself not fully understanding the concepts because of missing details.

автор: Claire L

4 мар. 2018 г.

Content was great but the grading issues with the homework assignments made this course very time consuming and frustrating. Will recommend it when grading issues are fixed.

автор: Jes T B K

9 февр. 2021 г.

Teaching and questionnaires are good. Programming assignments are low quality and wasting time. For the next module I will probably not bother much with the assignments.

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.