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Avis et commentaires pour d'étudiants pour Convolutional Neural Networks par deeplearning.ai

4.9
étoiles
34,595 évaluations
4,424 avis

À propos du cours

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....

Meilleurs avis

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.

AR

Jul 12, 2020

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

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301 - 325 sur 4,388 Avis pour Convolutional Neural Networks

par Jean D

Jul 09, 2020

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.

par Shivdas P

Jan 01, 2020

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.

par Gurubux G

Aug 20, 2019

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

par Gilad R

Aug 13, 2019

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.

par Bernard O

Oct 31, 2018

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.

par Stephen V K

May 17, 2019

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.

par Himanshu B

Jul 17, 2018

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.

par 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.

par 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 !!!

par 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.

par 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.

par 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.

par 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

par 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.

par 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..!!

par 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.

par 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!

par 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!

par 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!!

par 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.

par 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!

par 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.

par 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.

par 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.

par 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!