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Opiniones y comentarios de aprendices correspondientes a Convolutional Neural Networks por parte de deeplearning.ai

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32,071 calificaciones
4,046 revisiones

Acerca del Curso

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....

Principales revisiones

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.

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276 - 300 de 4,019 revisiones para Convolutional Neural Networks

por Luis A O A

Mar 20, 2018

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.

por Sai K S

Mar 16, 2020

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 !!!

por Fanyi D

Nov 18, 2019

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.

por Kurt K

Nov 27, 2017

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.

por Arkajyoti M

Jun 10, 2019

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.

por Alex B

Oct 12, 2018

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

por Arun P R

May 01, 2020

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.

por Aditya A G

Mar 17, 2018

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..!!

por Serzhan A

Nov 20, 2017

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.

por Elio M

May 03, 2020

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!

por Mihai P

May 29, 2020

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!

por Priya k

Apr 13, 2020

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!!

por Leonardo R C

Jun 01, 2019

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.

por Harold L M M

Nov 19, 2018

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!

por Yoan S

Oct 05, 2018

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.

por Xavier S P

Dec 20, 2017

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.

por Abhinav M

Jun 06, 2020

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.

por Arash A

Mar 15, 2020

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!

por 梁礼强

Apr 02, 2019

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.

por Nilanka W

Jan 14, 2018

This course taught how the latest computer vision systems works. The content is really great and the lectures and mentors have put a lot of effort in creating the assignments and notebooks, which are high quality. recommend to anyone who are interested in the field

por Rúben G

Oct 20, 2019

Through this course I understood how modern Computer Vision tasks are addressed with CNN. Also I learn that a CNN can be combined with a FCN. I further understand better the notion of the neural network and the advantage/disadvantage of having more or less layers.

por Michael F

Nov 01, 2018

The best in this series of courses so far. The maths was hard, and the programming assignments were accordingly at a higher level. But the applications of ConvNets are so fascinating, and their implications so profound, that I enjoyed every moment of this course.

por Pavan K V

Jan 19, 2018

the best course out of all 4 in deep learning.The best thing i liked most in this course is the applications such as

1) Image classification/Image recognition

2) Object detection-Automatic Car Driving

3) Face Verification and Face Recognition

4) Neural Style Transfer

por Zhao Y

Nov 25, 2017

This course gives me a deep understanding of CNN and also introduces me some latest information about face recognition. It makes me have an access to learn AI in an efficient way. Words seem to fail me when I want to show my gratitude to the teachers and mentors.

por Anshul M

Apr 29, 2020

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.