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Отзывы учащихся о курсе Convolutional Neural Networks от партнера

Оценки: 40,437
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.


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.

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401–425 из 5,334 отзывов о курсе Convolutional Neural Networks

автор: Gautam K

8 июля 2020 г.

This course is awesome. It helps in learning CNN in a very easy way. Concepts are taught in a fantastic way that makes it easily understandable. Programming exercises are designed in a way that makes typical concepts easy and is based on practical applications.

автор: Anshul M

29 апр. 2020 г.

The concepts of CNN and the attached algorithms have been explained clearly. I found the programming exercises to be one of the best way in order to get a first hand experience over implementation and understand the concepts required to build my own application.

автор: khalid w

10 нояб. 2019 г.

This course has helped me very much in understanding the nomenclature of convolution networks. Previously I struggled reading different research papers related to convolution networks as I was unable to understand the different dimensional changes in each layer.

автор: C I

23 дек. 2020 г.

This was a really good course. Somewhat more challenging than the previous courses of this specialization. My favourite part of this course would probably be NST part in week 4. YOLO algorithm part was the hardest. But overall one of the best courses available.

автор: Alex S

20 дек. 2018 г.

Exellent course for first experience with convolutional networks. A few mistakes that seem frustrating at the time you are completing course really help to gain better overall understanding. Thanks a lot for good work all the involved people, stuff and mentors.

автор: Sayar B

16 авг. 2018 г.

Perhaps the toughest course so far, Convolutional Neural Networks introduces us to computer vision. Professor Andrew explains complex, state-of-the-art cases where computer vision is being used today. Great programming assignments, great lectures, great course.

автор: Shifeng X

25 мар. 2018 г.

awesome course! the assignment is actually not just a piece of homework, it indeed a kind of guidance, give you detail step by step examples of how to code the learned algorithm. Thanks to the lecturer, didn't find any course more 'user-friendly' than this one.

автор: Abel G

7 нояб. 2017 г.

Wow.. what Can I say? This was the toughest of the three previous but super happy to be in this journey.

I learned a lot and I am motivated more than anytime to immerse myself in this field. There is so much to learn. Thanks to all the people behind this course!

автор: Ruby A

23 авг. 2020 г.

Excellent explanations of the theory and math behind the basics of CNN that anyone can understand easily. The assignments are also well designed in such a way that one could apply the theoretical knowledge gained to solve real time problems. Excellent course.

автор: Karthikeyan R

29 дек. 2019 г.

Again, excellent course from Andrew Ng! Made complex algorithms and concepts very clear! Got to know how CNN, Facial recognition and Object detection works. Reference to the literature paper will come handy in the future if one thought of diving deep into CNN.

автор: Julian S

20 нояб. 2017 г.

Excellent course. Concepts very clearly described. Only improvement would be more Tensorflow and possibly Keras training. Yes, you can go elsewhere for this, but Andrew Ng is so good at explaining, I'd expect he'd do a better job!

Many thanks Mr Ng and team!!

автор: Guruprasad K

16 февр. 2022 г.

This was the most fascinating course in the series. It is amazing how quickly new innovations like the YOLO algorithm have managed to reach mainstream within a couple of years. I would encourage all students to also supplement the learning from other sources.

автор: Timothy G

8 янв. 2021 г.

Very nice coverage of of CNNs with excellent examples and content on intuition. I also greatly appreciate the efforts of the instructor - he really does care about teaching the course and helping students - it comes through in his lectures and presentations.

автор: Reda M

7 апр. 2020 г.

Excellent course ! Theory and practice are covered in a relevant way, and Andrew's been very encouraging and clear all along this CNN journey ! The fun part is obviously art generation with the VGG19. Great thanks to Andrew and to the team !

автор: Yao F

19 мая 2019 г.

The course is pretty good with advanced techniques on computer vision. The only regret is one problem about the last coding homework. I failed to load the pre-trained model and can only finish the home work without checking the accuracy of designed examples.

автор: Pankaj D

25 дек. 2017 г.

Amazing course plan and delivery! Classic CNN architectures, ResNet, YOLO, face-recognition, neural-transfers - all in a very succinct package! Some very minor issues with auto-grading of assignments, but nothing that the discussion forums won't get you thru.

автор: Sagnik C

9 мая 2022 г.

This was a great course for learning the nittigrities of several concepts including CNNs, object detection, face recognition, etc. The ideas were presented in a lucid manner and the programming exercises were a great addition to the overall learning process.

автор: Ahammad U

18 окт. 2020 г.

Really great course in this deep learning specialization. I have enjoyed the entire course. Video quality is high and the instructor, Andrew is really awesome, I couldn't express in my word. Thank you Coursera for giving me the chance to complete the course.

автор: Jay R

27 янв. 2019 г.

Andrew's explanations, and the exercises are absolutely fantastic. There seems to be a lot of tricky math in Convolution Neural Networks and Andrew's explanations and illustrations help students understand the essential concepts behind each type of Conv net.

автор: Paul S

29 нояб. 2018 г.

Excellent course. Very good and well structured explanations by Andrew Ng: one concept per video, sometimes a second video to explain why the concept works or to give some intuition. Course covers many of the classis deep learning papers. Highly recommended.

автор: Joshua P J

7 авг. 2018 г.

Weeks 1 & 2 were very good. Week 4 was excellent with extremely clear presentation. I didn't like week 3; it felt like the topics were presented in random order, and the homework felt trivial (I finished it easily but I still have no idea what was going on).

автор: Camila B V

25 мар. 2020 г.

Awesome, I loved taking this course, the way to explain the topics is the best. I enjoyed every part of this course and the most important part I understanded several concepts. The exercises and material class are really usefull. Congrats you're the best.

автор: Kaan A

30 июля 2019 г.

This course was the greatest one among the first 4 courses of the Deep Learning Specialization. Real world examples were perfect. Moreover, the paper suggestions helped me a lot to learn through my process of this course. Thank you Andrew and Coursera Team.

автор: Michael G

16 нояб. 2018 г.

Great examples and walkthroughs. I didn't think I would be able to code all the various CNN architectures, but this course made that process challenging, but doable. Now it is time to start working on side projects to sharpen the skills I have learned here.

автор: Artem P

22 апр. 2018 г.

Probably the best course in the specialization (well, along with Sequence models). 50 layer VGG model built in Keras gives awesome enterprise-level results on a relatively small data sets..! But I recommend taking all these courses, they are all very good.