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Вернуться к Convolutional Neural Networks

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

4.9
звезд
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

OA

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.

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

Фильтр по:

551–575 из 5,347 отзывов о курсе Convolutional Neural Networks

автор: Dharanidaran

10 мар. 2019 г.

I gained the ability to read and understand research papers after taking this course. I you want to have a good course on Object Detection, Neural Style transfer, I would highly recommend this course.

Thanks Andrew.

автор: Elena B

16 нояб. 2017 г.

I really enjoyed the course. Thanks a lot for interesting and clear video material as well as for the exciting programming exercise. I have learned a lot and will hope to be soon applying this knowledge in my field.

автор: Janith G

7 окт. 2019 г.

Excellent Course. Programming exercises are really useful as they are mostly based on real world work done by experts. Thank you Prof. Andrew for trying to distribute knowledge on deep learning for students like us.

автор: chee y

22 апр. 2019 г.

Very detailed and thorough course on CNNs. The difficult concepts are presented in an easy to understand manner and the practical exercises allow you to gain a better understanding of using the various CNN networks.

автор: Cristina N

22 дек. 2017 г.

Well taught course, especially for those who want to develop some computer vision application with deep learning. The exercises in this course are a bit more complicated than the other courses of the specialization!

автор: David S B

3 дек. 2017 г.

As with the previous courses withing this specialization, this course delivers a pristine clear overview of this architecture both practically and theoretically. Excellent for getting on the ladder of deep learning.

автор: nicholas m

11 авг. 2021 г.

Prof Andrew's teaching style is second to none and very engaging. I thoroughly enjoyed the course especially given my limited programming background. Certainly learned a lot and hope to complete more of his courses

автор: Elham A

28 мая 2021 г.

I really enjoy this course. It covers most important aspect of computer vision so that I can watch these training videos and do these assignments over and over again and learn a lot every time. Thank you very much.

автор: Saswat K P

5 авг. 2020 г.

Awesome course. Learnt a lot from all the assignments and the video lectures. Lots and lots of concepts which really helped me learn the core components of building a CNN for different computer vision applications.

автор: Simon L

2 окт. 2019 г.

Learned a lot in this course. Some exercises were very hard to complete for misc reasons though. So expect some frustration with getting the exercises done. I certainly had my moments of frustration along the way.

автор: Leah P

24 апр. 2021 г.

Very informative. From basic builds of neural network to transfer neural network styles. every basic components are explained very beautifully. The instructor and the quizzes and assignments are well constructed.

автор: Abdulrazak Z

28 февр. 2021 г.

Amazing course. The course is very useful. The way the professor illustrate CNN and their uses makes you love this field. The applications you are going to do as well are REAL LIFE applications.

HIGHLY RECOMMENDED

автор: DEVANSHI K

24 сент. 2020 г.

This was a very fun course, the most interesting so far in the specialization, probably because computer vision has so many day-to-day life applications. I learned a lot through this course and really enjoyed it.

автор: Aman K

11 июля 2020 г.

One of the most challenging courses in the deep learning specialization. You will get to learn really cool stuff however it would be really helpful if you practice a bit of TensorFlow before or during the course.

автор: Shahzad A K

19 апр. 2020 г.

Excellent series of courses. Makes the mysteries of deep learning accessible to a lot of people who would otherwise be deterred by the cryptic nomenclature. Kudos to Andrew Ng and the entire deep earning.ai team.

автор: Rameses

14 дек. 2019 г.

Very Fascinating Course. After taking this course got insight into computer vision applications. Especially fascinating were the sections on autonomous driving vehicles, neural style transfer and face recognition

автор: raj m

17 июня 2018 г.

Great content to provide you in-depth knowledge of some of the really great algorithms and techniques used in Computer Vision. The citation of papers on the lecture slides is really helpful to explore the topics.

автор: Anand R

7 мар. 2018 г.

Excellent course with deep understanding . Had hard time to figure out many things on my own. I learned a lot. Thanks to Coursera for creating such a wonderful course, especially Andrew who is such good teacher.

автор: Davide C

9 дек. 2017 г.

The course was really interesting. I was really looking forward to learn about ConvNets. Prof. Andrew Ng way of teaching is easy to understand, as usual. I am really satisfied by this course. Thank you very much.

автор: Yahia E

15 июля 2019 г.

Great course. I thought I understood how conv networks work, but this course made me realize a lot of details and tricks that I wasn't aware of. It also increased my confidence by reading state-of-the-art papers

автор: Mohammad S

22 окт. 2020 г.

This is the best Course on CNN, I will learn such complex things in easiest way.

thanks to Deeplearning.ai and also huge thanks to coursera finential aid, because without that I could not learn such cool things.

автор: Bharat S S

4 сент. 2019 г.

CNNs is a fantastic course for anyone who wants to understand how deep neural networks are used for complex image based tasks like object recognition and localization, classification and neural style transfer !

автор: Pedro H

6 дек. 2018 г.

Beautiful depiction of convolutional neural networks: from the basic concepts, to their application in the context of computer vision. Great theoretical framework and application through thoughtful assignments.

автор: Supakrit B

16 апр. 2018 г.

A must course to get start in Convolutional Neural Network and Computer Vision. The instructor is very superb, teaching with the right level of detail while using real-world problem to enhance an understanding.

автор: Joshua B

26 мар. 2018 г.

Dr. Ng did a superb job going through the history of ConvNets. The examples, applications, and homework were wonderful, and I feel now much more skillfully able to read the scientific literature on the subject.