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Voltar para Convolutional Neural Networks

Comentários e feedback de alunos de Convolutional Neural Networks da instituição deeplearning.ai

4.9
21,388 classificações
2,624 avaliações

Sobre o 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....

Melhores avaliações

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.

EB

Nov 03, 2017

Wonderful course. Covers a wide array of immediately appealing subjects: from object detection to face recognition to neural style transfer, intuitively motivate relevant models like YOLO and ResNet.

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1 — 25 de {totalReviews} Avaliações para o Convolutional Neural Networks

por Gyuho S

Apr 25, 2019

This course is definitely tougher than the first three courses. Challenging but worth it.

por David B C S

Dec 17, 2018

Great course, easy to understand and very useful. The explanations are very clear, as is expected from the professor. The purpose of the course is for you to have a practical comprehension of CNNs, it will give you the necessary tools to implement you own networks, but it will not get into the specifics of each model. Nevertheless, all of the resources are referenced, which makes it very easy for you to dig deeper on any specific topic covered on the course.

por fabrizio f

Dec 17, 2018

Very good however most of the effort is applied in learning and applying programming (tf, Keras) than actually thinking about the DL models and practicing different scenarios.

por Aleksa G

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.

por Farzeen H

Jan 12, 2019

Amazing! Feels like AI is getting tamed in my hands. Course lectures , assignments are excellent. To those who are not well versed with python - numpy and tensorflow , it would be better to brush up.

por Cosmin D

Jan 04, 2019

Good content, videos have the occasional editing hiccups that also affect other courses in this specialisation. Assignments could be a little bit harder but do a reasonable job at familiarising with useful deep learning frameworks.

por Michael J

Jan 02, 2019

A short (but cogent) overview of CNNs with a ton of references to read through and much more interesting assignments (than previous courses). I really enjoyed this course, I got a ton of exposure from it.

por Tian Q

Jan 01, 2019

Excellent introductory course for CNN. The basic ideas and key components are explained clearly. Coding assingments helped me understand the algorithm to every little detail.

por Markus B

Dec 05, 2018

Great course. The only improvement I'd wish is to get a better introduction to the concepts of Tensorflow and Keras.

por Basile B

Apr 30, 2018

IoU validation problem is known but nothing as been done to resolv it

video editing problem

unreadable formula in python notebook for art generation (exemple :

$$J_{style}^{[l]}(S,G) = \frac{1}{4 \times {n_C}^2 \times (n_H \times n_W)^2} \sum _{i=1}^{n_C}\sum_{j=1}^{n_C}(G^{(S)}_{ij} - G^{(G)}_{ij})^2\tag{2} $$

What append ? that was great so far... =(

por Hrithwik S

Jun 19, 2019

An awesome course indeed

por Vaibhav M

Jun 19, 2019

excellent course but the content can be increased by including some more hot applications of CNN

por Tianqi T

Jun 19, 2019

the content of this course was very interesting and practical. however towards the end (week 4), there were a lot of confusions about how TensorFlow works.

por Jonathan E

Jun 19, 2019

This is an amazing course.

por Yikuan T

Jun 19, 2019

it's quite a useful course for a student who are interested in DL

por Hyunseok

Jun 19, 2019

It was awesome! You will never regret to choose this course!!

por Jiali H

Jun 18, 2019

the assignments have some bugs that sometime I could not find the "submit" button. Also, the links of "Hints" sometimes didn't direct to the right one.

por Salvatore S

Jun 17, 2019

Best Course I have done on Coursera!

por Catherine C

Jun 17, 2019

deeplearning.ai always provide great course.

por Sahil A

Jun 16, 2019

Awesome course by Andrew Ng

Could have more awesome if he had included some projects for showcasing on resume.

por puneet s

Jun 16, 2019

Really cool Course -:)

por Kenneth L

Jun 16, 2019

Some sentences get repeated twice maybe due to editing errors.

por Dien-Lin T

Jun 16, 2019

The explanation of the concepts is very easy to understand, and the assignments are really helpful.

por Yongseon L

Jun 15, 2019

https://www.coursera.org/learn/convolutional-neural-networks/programming/IaknP/face-recognition-for-the-happy-house/discussions/threads/NcpP7i95EemJswr-eOHMNg

por Jaime M M

Jun 15, 2019

As in previous courses, Andrew made understandable complex and abstract content. This course is by far more challenging than the 3 previous ones. Maybe not at the assignments as we make use of facilitating frameworks and helper functions, but to really follow what is happening behind... its another level compared to previous courses on the specialization.