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Отзывы учащихся о курсе Convolutional Neural Networks от партнера

Оценки: 41,220

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


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


11 дек. 2019 г.

Great Course Overall

One 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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376–400 из 5,441 отзывов о курсе Convolutional Neural Networks

автор: Bharath C

23 окт. 2020 г.

This course is really informative on various concepts of CNNs and I believe it is a must for any beginner starting in Deep learning to start with this course to understand the overall applications as well as the procedure and programming involved in each of those concepts.

автор: Arkajyoti M

10 июня 2019 г.

Thank you so much for this wonderful course.

I have only one suggestion there's a lot of bugs in the notebooks, especially the last one Week 4 Happy House Face recognition. Please fix that as a lot of weights are missing and completing that exercise involves a lot of hacks.

автор: Alex B

12 окт. 2018 г.

The most challenging course in the series so far, it was also the one that helped me best understand how these networks function. I have already recommended this course to colleagues, and think it is the perfect course for an intro to computer vision, tensor flow and Keras

автор: Trijudi M S

26 мар. 2022 г.

great references and explaination. with this course, i getting more knowledge about Convolutional Neural Network, like to many type CNN (AlexNet, GoogleNet, ResNet, etc). i curious about image segmentation and landmark detection. thanks for giving me to learn this course

автор: Arun P R

1 мая 2020 г.

Its is the finest and greatest course I have ever seen on Convolutional Neural Network. It feeds a lot of intuition on the field of Computer vision and CNN impact on it. It goes through many state of art algorithms and revolutionary implementations of Deep neural network.

автор: Soumyodeep D

3 дек. 2020 г.

Great Course!! Just completed it. Really a good course for beginners who want a jump start in CNNs. Without the theory given in this course, it will be really difficult for someone to implement Convolutional Neural Nets in practice using Tensorlfow or any other library.

автор: Ruthuparna K

25 авг. 2020 г.

I am thoroughly satisfied with this course, as it gives a very in-depth knowledge into CNN and their applications, while also giving an introduction into TensorFlow and Keras. Andrew Ng is amazing as always. I loved the interesting things we got to do in the assignments.

автор: aditya g

17 мар. 2018 г.

Very nicely prepared and presented. Assignments gives good insights into concepts learned while for yolo,neural styles, face recognition problems eagerly looking for building CNN architectures from scratch & training them in future courses. Thanks a lot Andrew & Team..!!

автор: Serzhan A

20 нояб. 2017 г.

The best course in the series so far. Andrew Ng makes the complicated seem easy and does so by dividing the topics into small digestible pieces. You will binge-learn his courses because of how addicting and gratifying the experience of learning is made by the instructor.

автор: Nguyễn V A

27 июня 2021 г.

This course is excellent! I would recommend this course if you love CNN and want to know more about it. Personally, I would like to thanks Andrew Ng and all the equipes for providing such an amazing content. Besides, thanks for giving me the chance to learn this course!

автор: Danilo B

8 авг. 2020 г.

This course is perfect at introducing a newcomer to CNNs and at the same time covering many applications of this type of neural network. I like how even though the papers mentioned are sometimes 5 years old Professor Ng and the team is able to create such a good course.

автор: Eung P

15 мая 2021 г.

An excellent course on CNN! After watching Professor Andrew's video lectures and trying related programming work, I was able to gain a reasonable amount of confidence on the various concepts, which otherwise could have been overwhelmingly difficult and complicated.

автор: Elio M

2 мая 2020 г.

Great course once again! It would benefit by having the programming exercises for weeks 2-4 somewhat less trivial, in order to trigger more thinking on the different solutions and how/why they work. It remains still another great piece of work by Andrew Ng. Thank you!

автор: Steve C

20 дек. 2020 г.

great course with detailed description of the convolutional network concept with many practical examples. Neural Style Transfer was probably one of my favorite programming exercise for machine learning taken in Coursera. Thanks to the staffs for creating this course!

автор: Mihai P

29 мая 2020 г.

This course exceeded my expectations. It is very robust and covers a lot of state of the art topics that are really used nowadays. I'm really excited about the knowledge i've gained from this course because it offered a great value that cannot be measured. Thank you!

автор: Priya K

13 апр. 2020 г.

This course is really amazing. I would highly recommend this course!! It gave me a clear insight into several concepts like Face recognition. The video lectures covered all topics in detail. I would like to thank the instructor for providing such a wonderful course!!

автор: Leonardo R C

1 июня 2019 г.

This is a very interesting and fun course to take. You put into practice all the knowledge from previous coruses from the specialization and apply them in applications that are changing the world right now. As usual, professor Andrew explains every concept perfectly.

автор: Harold M

18 нояб. 2018 г.

The best course by far in this specialization. This course covers all the important topics in Convolutional Neural Networks, face verification and face recognition.

You have to work very hard to complete it. Thus, it's a great challenge!

Thank you Professor Andrew Ng!

автор: Yoan S

5 окт. 2018 г.

These courses are VERY well put together and concentrate excellent concept in little time compared to taking the available Stanford CNN classes online which are verytime consuming for the same result. Andrew is motivating and makes difficult concepts very accessible.

автор: Xavier S P

19 дек. 2017 г.

The idea of inserting convolutions into the net and in the back propagation is really cool yet so simple to implement after watching those lectures. It makes sense why image simplification via convolution in layers can greatly help performance in a deep learning net.

автор: Harold J C O

7 июня 2021 г.

This course is exceptional, I learnt important topics for the career path that I'm trying to build in AI, I appreciate to all the team of DeepLearning.AI for the effort creating this amazing course, I recommend to anyones that wants to know fully details about CNNs.

автор: Ching-Cheong L

25 окт. 2020 г.

Very great introductory course. Since I am not familiar with tensor-flow, there is still a gap for me to fully understand everything in the programming exercises. But this also lead me to a clear direction what's next to me, thanks for the team creating this course!

автор: Abhinav M

6 июня 2020 г.

I really love the instructor. He is the best teacher and a mentor. He has taught me a lot. I was nothing in Deep Learning, but the way he taught me inspired me of deep learning and machine learning. Now I am seeking my career completely into it. Thanks to Andrew Ng.

автор: Arash A

15 мар. 2020 г.

Such an amazing course. Andrew is such a great instructor. Actually, it is thanks to this course and the whole Specialization that I'm making now my own career as Chief AI Scientist for a Health Tech Start Up.

I'm endlessly grateful to Andrew and this Specialization!

автор: 梁礼强

2 апр. 2019 г.

this course is pretty good,but the some of these techniques introduced in class are slightly out-of-date,such as yolo v2 and this version of neural style transfer. It's OK as an introduction, but it may be better to mention the latest or general version algorithms.