Chevron Left
Вернуться к Convolutional Neural Networks

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

4.9
звезд
Оценки: 28,418
Рецензии: 3,434

О курсе

This course will teach you how to build convolutional neural networks and apply it to image data. Thanks to deep learning, computer vision is working far better than just two years ago, and this is enabling numerous exciting applications ranging from safe autonomous driving, to accurate face recognition, to automatic reading of radiology images. You will: - Understand how to build a convolutional neural network, including recent variations such as residual networks. - Know how to apply convolutional networks to visual detection and recognition tasks. - Know to use neural style transfer to generate art. - Be able to apply these algorithms to a variety of image, video, and other 2D or 3D data. This is the fourth course of the Deep Learning Specialization....

Лучшие рецензии

AG

Jan 13, 2019

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.

RK

Sep 02, 2019

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:

151–175 из 3,398 отзывов о курсе Convolutional Neural Networks

автор: yuji w

Nov 16, 2017

nice program to learn about convolutional neural works. I always fascinated about convolutional networks and this course gives me the very nice introduction and sort of in-depth knowledge and first hand programming knowledge in this area. The instruction and nice and start from easy and slowly get you into the deep knowledge. Great course and nice work.

автор: Daniel C

Feb 01, 2018

This course covers the basics of convolutional neural networks. After you understand the materials covered in this course, you'll know how smart phone cameras auto focus on faces. You'll also learn the basic building blocks that powers self-driving technology. These are just two of the many cool concepts you'll learn in this course. Highly recommended!

автор: Cem O

Apr 10, 2018

Just like the other courses in this series, this course was prepared with great care to optimize the learning outcome. Clear and motivating lectures, great selection of up-to-date methods and very illustrative examples. I would like to thank Prof. Andrew Ng and all the course staff most sincerely for designing and making available these great courses.

автор: abhishek a

Aug 09, 2019

Excellent Course!! By doing the this course I am now feeling very confident in CNN. This course is very important for all whether they may or may not work in CNN/images. This fundamental learnt here can be used in other domains of deep learning.

Thank you deeplearning.ai Team for proving this wonderful course. It has opened new opportunities for me.

автор: Pin Z

Jun 24, 2018

This is a very good course to get to know the basic concepts of CNN and to start hands-on programming to implement CNN. Andrew's lecture gives very clear explanation of the principles of CNN, as well as introduction to state-of-the-art example network structures. The exercises help to build essential skills to program CNN using TensorFlow and Keras.

автор: Youssef H

Apr 10, 2018

I have really learned a lot from taking this course. During the course you will be exposed to the state of art deep learning architectures by understanding the theory behind them in lectures and then you will get to implement them in the assignments. I have taken the first three courses and I think that definitely this course is by far the best one.

автор: Hector L

Feb 01, 2020

I enjoyed this course. I learned a lot about Convolutional Networks and the assignments were very fun to complete. The assignments are difficult enough to lay the groundwork for the subject - but you definitely need to take your time to understand and probably run experiments on your own.

I loved the ResNet, YOLO, and Face Recognition assignments.

автор: Yogesh C

Jun 03, 2019

This course was amazing and interesting. The tutorials and quizzes were great. But I was looking for the implementation of CNN from scratch without using tensorflow.

Rest as mentioned this was an amazing course. Now, I have a better understanding of YOLO algorithm, face recognition, Neural style transfer. Thanks to Andrew and the rest of the team!

автор: Sadam H

Dec 20, 2019

Learned some interesting concepts about different state-of-art ConvNets. Although I was hoping that in Face Recognition Programming exercise there would be some code implementation exercise or example about one-shot learning and Siamese network, it would have been perfect. Nonetheless, very nice structured course to learn intuitions intuitively.

автор: Abanoub A

Sep 22, 2018

The Way Prof. Andrew explains things, taking us from simple stuff to the complex conclusions by ourselves making it so much easier and convincing!

The course content was great and assignments were fun, I like that in the end of each assignment there is always a cell that's like a "playing ground" allowing you try and test the models you created.

автор: Hardik V U

Aug 19, 2018

This course is good from both the perspective: Research and Development. This course involves many real life applications which will help us to understand the real life problems and also will help in tacking such problems. So, I would strongly suggest to go for this course which builds the fundamental for computer vision and pattern recognition.

автор: balaji

Dec 25, 2017

As a beginner I have learnt a lot of topics with good clarity. Assignments have given me good understanding of the topics learnt.

I think the assignments should some more difficult and students should be able to spend some more time understanding the code and writing code of their own.

Thank you very much for making learning affordable and easy.

автор: William v

Dec 07, 2017

The libraries needed such as tensorflow, might need to better support (a special segment on them beyond the overview). Those models are complex and deep and using those libraries wasn't clear to me even though I managed to get the solutions, I needed time to study those libraries and they are rich and complex. I enjoyed the course immensely.

автор: Wanda L

Feb 16, 2020

Fantastic course about Convolutional Neural Networks! For me the best part of the course (and the specialization, too) is the assignment. You could hardly find a similar friendly, supported and easy-to-follow homework elsewhere in the world, even in some universities. Thanks to Andrew, and thanks to all teaching assistants in the community!

автор: Eddy P

May 27, 2019

All are pretty good! Except for the low speed while running the training process which I think have in fact hurt the course's completeness. Because we have skipped many important training processes and instead use pretrained models to save time. I suggest maybe we can collaborate with Google and put the programming assignments on the Colab.

автор: Tu L

Nov 07, 2017

Another amazing course from Prof Andrew and his colleagues. I've had a very exciting time to get to know about various CNN architectures, as well as to be able to implement, even just small part of them, and to make them work in practice. Thanks deeplearning.ai team a lot and look forward to seeing other courses from you in the near future.

автор: Harshavardhan S

Nov 05, 2017

Awesome Course...You have gone out of your way to make the programming exercise simple enough for beginners to get a taste of very recent algorithms. thank you for your effort. I really loved the course. And it has given me enough to get me interested in and capable of following Computer Vision literature on my own with greater confidence.

автор: Prakash M

Feb 14, 2020

Wonderfully designed course for beginners to know all about CNNs. Even experienced professionals can have all their concepts cleared not only in CNNs, but also in YOLO and it's applications in object detection. Thank you very much Coursera Team for all your efforts in making this course accessible to thousands of aspiring data scientists.

автор: Yedhu K V P

Jun 29, 2018

This course helped me to learn in detail about convolutional neural networks. I have heard of CNN, but this is the first time I am trying it out myself. It's interesting and fun to learn. I'm planning to do more projects using the ideas learned from this course. I highly recommend this course to any aspiring machine learning student.

автор: Muhammad M K

Feb 23, 2018

An amazing course! Not only does the course covers seminal work in the area of deep learning related to image processing but it shares valuable insights into problem solving and provides hands on experience. If there is a single course that I have to recommend to anyone related to deep learning for image processing, this would be it.

автор: Rajthilak M

Apr 23, 2018

The lectures were excellent and helped me understand the key elements of convolutional neural networks. I enjoyed coding the assignments and building foundation knowledge for building real-world AI applications. Thanks to the very strong foundation ,I am able to read and interpret many of the real world AI experts' blog and views.

автор: Deleted A

Nov 27, 2017

This is really a superb course. Andrew Ng has the ability to clearly explicate the complexities of convolutional networks. The coverage of topics such as residual networks, face recognition, Yolo, and neural style transfer are both intriguing and informative. I found the programming assignments challenging, but deeply instructive.

автор: Irina M

Apr 02, 2019

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

Aug 15, 2018

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: Wei W

Jan 10, 2018

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.