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Вернуться к Convolutional Neural Networks

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

4.9
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Оценки: 41,215

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.

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251–275 из 5,441 отзывов о курсе Convolutional Neural Networks

автор: Minsheng L

11 апр. 2020 г.

a really nice class. I learned different techiques like CNN, YOLO, and used them to do face recognition, style transfering.... This calss is comprehensive. I need repeating many time before I can really master all of them. Thanks for the instructors, and all the people who have contributed to this calss. I've really learned a lot.

автор: Irina M

2 апр. 2019 г.

Thank you for the course and I really like it. Learn a lot and I made few teaching sessions of DeepLearning algorithm for Women Who Code, where I am mentor in leadership group. I clarified many things for myself during the course, I very grateful for the amazing knowledge and experience! I will recommend this course to colleagues.

автор: Tun C

15 авг. 2018 г.

I appreciate the way professor Ng made the Convolutional Neural Networks concepts and architectures easy to understand. This course gave a very good overview and professor Ng presented the intuition behind the concepts as usual. The programming assignments are also a good mix of under-the-hood and high-level application of CNN.

автор: K173664 S K

9 февр. 2021 г.

This was a great course, thousand thanks to sir Andrew ng who put a great effort in structuring and delivering the course in a way that is easy to be digested for professionals as well as for beginners. there are a lot of cov net courses in the market but the knowledge and understanding I gained from this course are unmatchable.

автор: Gabriel M

13 июня 2020 г.

A good course, i feel like it only grasps the surface of the subject, but very good, feels way too easy should remove the rails because it feels way too streamlined and gives you very little room to wiggle, but the video content was very good and gives you the tools to understand the papers and the investigation on the subjects.

автор: Hesham H

17 окт. 2021 г.

This among the rest of this specialization courses is the best.

A handful of loaded information, strong course materials, very intuitive quizzes, and the best practice programming, feasible for TensorFlow programming. Overall, I feel really grateful for taking this course, not to mention the rest of the specialization for sure.

автор: 김홍숙

7 сент. 2020 г.

As EXCELLENT as other courses in deep learning specialization.

Must do progamming assignment by yourself to get hands-on experience and deeper understanding of what you learned from lectures.

I would like to express my sincere appreciation to Prof. Ng and all staffs who prepared this excellent course and programming assignments.

автор: Felippe T A

21 мая 2020 г.

A great course!! The content was very deep and it was presented to us some important CNN. For me, for this course be better, it needs a final project, but I can understand due to the large amount of content. But, in general it is a great course, maybe the best available on the internet. Thanks Coursera, thanks DeepLearning.ai.

автор: Dinesh T

27 мар. 2021 г.

This was one of the most interesting courses. Fun part and what I loved most is learning about the Neural Algorithm of Artistic Style - Neural Style Transfer (NST) algorithm. Would love to spend lot of time doing much deeper into the algorithms and mathematics behind it, so that I could build something meaningful and useful.

автор: Jack W

10 янв. 2018 г.

This is a great intro to deep learning/AI course. Professor Ng has a way to explain things in a way that is super easy to understand. Basic knowledge (college level, but no need to be math/cs major) on linear algebra is required. If you are in science/engineer major, and took any kind of linear algebra class, you will be OK.

автор: keerthi k

21 февр. 2020 г.

Thank you so much Coursera. I have been doing this specialization properly, but suddenly I had an accident which took almost 10 days to become normal. During those time several assignments were overdue, but Coursera extended their assignments deadline twice and helped me complete this course. So once again I thank Coursera.

автор: Abhishek S

4 февр. 2019 г.

The CNN is always found as one of the trickier concepts to follow and it was actually very hard for me to figure out what these Conv layers are doing. But this course is so robust and easy to follow that I was even able to read the research papers on advanced CNN architectures with relative ease. Thanks to Andrew and team.

автор: ANSHUMAN S

4 июня 2019 г.

It has been a great journey through learning CNNs it was quite interesting rather than all other courses and I got to know really very new ideas which i can implement in my own models.

Once again I want to thanks Andrew Ng and all other teachers of Course

and a special thanks to Coursera for giving me this ample opportunity

автор: Nick H

22 мая 2019 г.

Awesome course if you want to understand the basics of CNNs along with recent applications of these algorithmns.

As usual, both Andrew's material and his presentation style kept me both engaged and interested to a point that I got ahead of the weekly schedule...which is probably a good metric in terms of course success

автор: Nikhil V K

20 окт. 2019 г.

Great course by Andrew Ng sir. It gives us a great insight into many case of studies of state of the art ConvNet. Gives us a lot of intuition about object detection systems in autonomous driving and landmark detection , one shot learning for face recognition and a fun way of applying ConvNets for neural style transfer!

автор: Wang F

14 янв. 2018 г.

Despite the confusing bug and server running problem in the last assignment of happy house ,

the course is still great . Compare to the other three ones, it's the hardest course for me by now .

You may feel stuck in some practice questions and program .Worth spending time to review the

stuffs of the course again。

автор: Pawan S S

8 янв. 2021 г.

One of the best courses I found to learn convolutional neural networks as a beginner. All the subject matter are well structured and the flow of the module is very easy to follow and understand. Together with the programming assignments, I was able to quickly grab the essentials of CNN. I highly recommend this course.

автор: Edson C

3 сент. 2020 г.

This was the most difficult course I did in this specialization, but I loved it, I loved it very much. Thank you very much dr. Andrew and coursera for the opportunity, I really understand the importance of studying computer vision and this course was very useful in this journey. Thank you very much, I really loved ...

автор: 杨建文

10 янв. 2018 г.

The last 2 courses were delayed, but the positive side for me is that, in the beginning I proceed too fast and didn't learn that well, the delay made me take more time on such a valuable course, carefully reading and memorizing the instructions of assignments. I'm really grateful for Prof. Ng's excellent instructions.

автор: Adam F

1 нояб. 2021 г.

I completed the entire specialization and having nothing but good things to say. Highly recommend it! Lectures are engaging, and Andrew does a fantastic job explaining some very complex topics. Programming assignments are challenging in a good way. You’ll really feel like you’ve learned a lot by the time you’re done.

автор: Sai K M G

23 июня 2020 г.

This Course was exceptional and upto mark. I learnt a lot of stuff easily and was able to implement into the real world example. This was really helpful for building up my resume. I thank Andrew Ng and Coursera team for giving financial aid to take up this course. The amount of knowledge gained is so valuable to me.

автор: Eric C

23 июня 2019 г.

Awesome. This course was much more dense than the other ones, there is so many areas to review. Since this course is about my favorite subject, I will need to pause and rework on each individual points and associated papers (yolo, nst, similarity learning) which will probably take me weeks... Prof Andrew is the best

автор: Arvind N

2 нояб. 2017 г.

I thoroughly enjoyed taking this course. Beautifully designed...Thank you!

I had written a detailed review of the first 3 deeplearing.ai courses at : https://medium.com/towards-data-science/thoughts-after-taking-the-deeplearning-ai-courses-8568f132153

I will review this CNN course as well, in the form of a blog post.

автор: Benjamín V A

9 июля 2020 г.

Great course, provided many clear explanations I has been searching before. The one thing they could improve is that some of the practical exercises seem more focused in the framework than the algorithms. (I spent more time googling how to pass parameters to specific functions than actually using the algorithms)

автор: Wade J

25 мар. 2018 г.

Good amount of challenge for after work learning. Nice exposure to different applications of AI. Fun.

Andrew Ng is awesome at explaining the concepts. Almost anybody would be able to understand them after he presents them. I also appreciate how genuine he is. You can trust that there is merit to what he tells you.