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Отзывы учащихся о курсе Convolutional Neural Networks от партнера

Оценки: 40,433
Рецензии: 5,358

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


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.


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.

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426–450 из 5,333 отзывов о курсе Convolutional Neural Networks

автор: Guillaume G

15 нояб. 2017 г.

I really like how Andrew Ng is able to explain actually pretty complex concepts in a comprehensible way, built on the knowledge of the previous weeks content.

Also great is the integration of recent techniques: inception modules/networks, residual networks.

автор: Amit A

27 дек. 2019 г.

Excellent course. Professor Andrew Ng ensured easiness in following the courses, highlighted important aspects and the assignments were very well structured. I am glad to have taken up this course and I hope to start using my learning in the coming months

автор: Chetan P B

8 мая 2020 г.

Amazing!! The assignments very well cover the concepts taught in video lectures and each part of the convolutional network is explained in detail. The First 2 weeks are quite full of concepts. I enjoyed the last 2 weeks covering the applications of CNNs.

автор: Daniel D

4 янв. 2019 г.

Andrew Ng's courses and Geoffrey Hinton's are about as good as courses get--rigorous, practical, and yet fairly thorough in the underlying theory. Convolution Neural Networks is certainly no exception to that as he goes into res nets and inception nets.

автор: Jesús A G S

24 янв. 2021 г.

It’s an excellent course, and also a lot more difficult than the previous ones. The only little problem is that in some programming exercises there are some fallen links to the web-information of some functions, complicating a little more the exercises.

автор: 谷雨

3 нояб. 2017 г.

It's really a great course that I've waited for so long! Thanks a lot for providing the well-organized and easy -understanding materials for those new starters of deep learning like me! Hope to see the last part of sequence models in the nearly future!

автор: Alexandre B

23 июля 2021 г.

Very well structured course & with Andrew Ng as the teacher, you really can't go wrong.

The assignments are extensive and help you put the thoery in practice.

I highly recommend this course for serious learners who want to advance in their AI learning.

автор: Aniket T

26 июля 2020 г.

The course was great you'll get intuition and deep understanding of how convolutional network work.... The material was missing segmentation part and assignment can be moved to tf 2.0... Overall it was great course and the assignments were also great.

автор: Aaditya S

3 июля 2020 г.

The instructor was great, also the assignments were really a helpful one. I would really appreciate the instructor making CNN such an easy and interesting topic. Even the content of the syllabus was also great and hence I enjoyed the course even more.

автор: EricNunn

21 янв. 2018 г.

The Neural Style Transfer assignment could benefit from some better descriptions and coding direction, but overall I loved all the assignments and learned a lot. I would like to learn more about Face Recognition and other Image Detection applications.

автор: Sonny R

29 июля 2019 г.

This provide me with a much deeper understanding of CNN and the basic building blocks for building CNN and facial recognition. I really enjoyed the programing exercising and learning how to do leverage additional frameworks like TensorFlow and Keras.

автор: Jack S

20 июля 2019 г.

Great course! I learned so many stuff. Andrew's lectures are very intuitive and helpful. Those Jupyter notebooks are definitely worth time exploring. One last thing is that I wish some limits of the current CNN model can be mentioned for big picture.

автор: AMRICHE A A E

3 мая 2019 г.

Another great course in the Deep Learning specialization. It's been a wonderful experience diving into computer vision and discovering some exciting new applications and concepts.

Many thanks to the course team and a special thank you to Dr. Andrew Ng

автор: Luisa F V C

5 авг. 2020 г.

In my opinion, this course is the most important and complete of the specialization course. Really, Andrew explains all the concepts necessary to create your own CNN or improving exist CNN. I loved this course. I know will be very useful in my Ph.D.

автор: Ratchainant T

15 мая 2018 г.

I really learn a lot from this course. However, It would be great if the course introduce how to annotate images and read annotated images to data set in order to get start computer vision project from scratch for audiences who has zero experiences

автор: Ocin L

8 апр. 2018 г.

Great course which gives me a basic understanding on the technologies behind object detection, face recognition. Also, the programming assignments are very useful and give me hands on experience on how to build a basic system using the technologies.

автор: Alexander K

29 янв. 2020 г.

Sometimes I had to close browser 1-2 times to make Kernel working during the submission of programming assignments. Interrupting or restarting the kernel was not helping. I'm sure it is not related to the course content, but just a technical issue,

автор: Karan S

5 сент. 2019 г.

The understanding of Deep Networks for Computer Vision gave me boost to go ahead and use them. I got some awareness about Keras, but I am a bit confused that should I stick with Tensorflow or with Keras. I Loved to work with Tensorflow in Course 2.

автор: Bogdan G

12 мар. 2019 г.

Excellent course on CNN which gets you familiar with many popular models from 2012-2016 including all the basic CNN models LeNet, AlexNet, VGG, Inception, ResNet, object localization/detection and YOLO, Face recognition with DeepFace, etc. Thanks!

автор: Rahul K

22 авг. 2018 г.

The best course among whole specialisation. One gets to learn a lot about image processing as well as a whole set of reading materials with every programming assignment. Go through the reading materials if you want in depth knowledge of some topic.

автор: John P

12 нояб. 2017 г.

As always, Andrew Ng manages to make the relatively complex seem simple. The programming assignments are excellent for demonstrating some diverse applications of deep learning and the optional backprop for conv layers was particularly illuminating.

автор: Bradley W

19 дек. 2017 г.

Great course that gives insight in CNNs. The coding in frameworks is sometimes confusing and there were some bugs in the face recognition lab, but these are minor compared to the value of the course. Many ideas presented are state of the art.

автор: Shyam P

9 мая 2020 г.

This is the best course I have ever had on Coursera. The assignments and the lectures are amazing. After completing this course, I got the confidence that I am not far away from becoming a data scientist now. Thankyou Andrew Ng sir and the team

автор: Stephen M

20 июля 2018 г.

This was a really exciting course, presented in a way that was clear and is easy to understand. It is great that it uses such widely used frameworks such as TensorFlow and Keras — which will make the learning quite applicable to the real world.

автор: Moaraj H

23 окт. 2018 г.

It was good, but a few broken parts in the assignment almost made me quit. Once fixed it was the normal extremely useful, introduction into very cutting edge stuff. Thanks for putting in the work for this guys, it really is an amazing resource