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Вернуться к Convolutional Neural Networks

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

4.9
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Оценки: 40,626

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

AG

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.

RK

1 сент. 2019 г.

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.

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351–375 из 5,361 отзывов о курсе Convolutional Neural Networks

автор: Siraprapa W

10 окт. 2021 г.

Prior to this course, I have been thru so many other elearning about the exact same topics, but none have them gave such a crystal ,clear, and easy to understand explanation. It is very enjoyable learning journey. Thank you, Andrew and the content team for such a wonderful jobs!

автор: Hasaan A

30 июля 2020 г.

Learned some really exciting stuff. It was great to learn a lot of the classical networks like resnet etc. Although, I wish the programming exercises did not have most of the stuff already filled in (though I understand it is done to make it easy for beginners to complete them).

автор: Dave J

6 апр. 2020 г.

The material is clearly explained by Andrew Ng in his calm yet enthusiastic style. Programming exercises are well structured and explained: if anything I find there's too much hand-holding but having got the basics, there's nothing to stop you experimenting further on your own.

автор: Animesh S

21 мая 2019 г.

Great course, concisely conveys both techniques and advice for practical implementation of Neural Networks in Image recognition. Great for a person who is already familiar with the idea of Deep Learning and want to take it forward, and ties in perfectly with the specialisation.

автор: Ali S

10 авг. 2018 г.

This course is a perfect way to teach these high-level concepts. They made it easy, step by step, and practical. You can learn not only convolutional neural networks in both conceptual and practical way, but also a lot of tips and tricks about tensorflow, Keras and even python.

автор: Moaz M

1 янв. 2021 г.

one of the best fundamental courses that I ever attended, this course will build the basic knowledge for CNN and computer vision, and will help those who wanted to start a career in computer vision

for me, I was really happy during learning object detection and YOLO algorithm

автор: Jean D

9 июля 2020 г.

Really amazing to get access to state-of-the-art deep learning science (and art) ! A right mix of general information, science and practice, together with the references to the articles describing precisely the technicity of what we discover ! Thanks so much to all the team.

автор: Abdullahi Y

26 мар. 2022 г.

This course is well organized and as someone with an intermediate level of experience with computer vision, I find this course very interesting and insightful. I really do recommend taking this course whether you're a beginner or a professional. Thanks for making this course.

автор: Shivdas P

1 янв. 2020 г.

The course is well structured, especially the exercise where one has to code the complete CNN example. It gives good insights on how to use the frameworks such as TensorFlow and Keras. Feel comfortable in understanding the concepts around CNN and it's implementation using TF.

автор: Gurubux G

20 авг. 2019 г.

One of the toughest and most exciting Course I have completed on the internet. Thanks a ton Andrew! I wish I can work with Deeplearning Team someday, so that I can learn every week, every day and probably explore the deepest of the Learning ocean potential that the team holds

автор: Gilad R

13 авг. 2019 г.

I really liked the dive into academic literature combined with the wide view of CNNs across various applications. The programming exercises were very revealing and informative, although a little more guidance on TensorFlow technicalities would have helped accelerate learning.

автор: Bernard O

30 окт. 2018 г.

This is quite a challenging course. Critical lessons on convolutions are the biggest value to me on this segment of the course. Takes a lot of the mystery out of CNN, but need to work hard at it. A very rewarding experience but does come with a few tear-my-hair-out incidents.

автор: Stephen V K

17 мая 2019 г.

The course does an very good job of explaining the concepts behind different types of neural networks, but the homework assignments pretty much only test these concepts. Students should not expect to gain any significant experience coding neural networks in keras/tensorflow.

автор: Himanshu B

17 июля 2018 г.

This is must course for the ones who really want to move into deep learning and the most important part of Deep learning and machine learning. So much informative and the best part is practical implementation where learning is so much great and informative with instructions.

автор: Luis O

20 мар. 2018 г.

I had only a little knowledge of CNN and struggled to grasp some concepts but after watching the lectures only once I can confidently explain the structure of a CNN and even compute the dimension of the layers on the fly thanks to the quiz questions. Totally would recommend.

автор: Sai K

16 мар. 2020 г.

I'm very glad that I chose Deeplearning.ai to learn AI. Andrew not only helped us learn the state-of-the-art techniques but also encouraged us to experiment and explore the concepts. I definitely am looking forward to complete the full specialization. Thank you Coursera !!!

автор: Fanyi D

17 нояб. 2019 г.

Prof. Andraw Ng is very good at presenting the core ideas to audience in simple and intuitive words and this course is especially useful for engineers with different background to step into or refresh some principles of the CNN. I personally strongly recommend this course.

автор: Kurt K

27 нояб. 2017 г.

A clear explanation of a difficult subject with an emphasis on being able to create and to understand your own neural networks.- Plus in this module how to use algorithms which significantly reduce your computational needs and with an introduction to processing visual data.

автор: mcvean s

11 нояб. 2020 г.

This course was an amazing experience! Learning with one of the greatest minds in the field, and the simplicity of this course to cover the topics in depth is exceptional. Everyone interested to dive into the field of CNNs and Computer Vision will benefit from this course.

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.