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Voltar para Image Noise Reduction with Auto-encoders using TensorFlow

Comentários e feedback de alunos de Image Noise Reduction with Auto-encoders using TensorFlow da instituição Coursera Project Network

4.7
estrelas
105 classificações
15 avaliações

Sobre o curso

In this 2-hour long project-based course, you will learn the basics of image noise reduction with auto-encoders. Auto-encoding is an algorithm to help reduce dimensionality of data with the help of neural networks. It can be used for lossy data compression where the compression is dependent on the given data. This algorithm to reduce dimensionality of data as learned from the data can also be used for reducing noise in data. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and Tensorflow pre-installed. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

Melhores avaliações

NL
7 de Abr de 2020

Really great learning for beginners. Through project learning it gives very good confidence. But rhyme desktop should be available until completion of project.

NS
15 de Ago de 2020

nice presentation skill, it is helpful for me to noise reduction and image processing

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1 — 15 de 15 Avaliações para o Image Noise Reduction with Auto-encoders using TensorFlow

por Narendra L L

8 de Abr de 2020

Really great learning for beginners. Through project learning it gives very good confidence. But rhyme desktop should be available until completion of project.

por Ravi P B

17 de Abr de 2020

A nice and short project and a good way to built a simple autoencoder and neural network classifier and getting them up and running.

por noman s

16 de Ago de 2020

nice presentation skill, it is helpful for me to noise reduction and image processing

por Kolawole E O

11 de Out de 2020

Teachable and Readable course.

Thanks so much!!

por SUGUNA M

19 de Nov de 2020

Good project based course

por nilesh n

28 de Mar de 2020

Crisp and useful!

por XAVIER S M

2 de Jun de 2020

Very Helpful !

por SUMIT Y

9 de Jul de 2020

Fine !!

por Kamlesh C

7 de Ago de 2020

Thanks

por sarithanakkala

23 de Jun de 2020

Useful

por p s

23 de Jun de 2020

Super

por tale p

17 de Jun de 2020

good

por Rohit M

13 de Jun de 2020

NICE COURSE :-))

por NAIDU P S A

27 de Jun de 2020

nice

por Jorge G

25 de Fev de 2021

I do not recommend taking this type of course, take one and pass it, however after a few days I have tried to review the material, and my surprise is that it asks me to pay again to be able to review the material. Of course coursera gives me a small discount for having already paid it previously. It is very easy to download the videos and difficult to get hold of the material, but with ingenuity it is possible. Then I recommend uploading them to YouTube and keeping them private for when they want to consult (they avoid legal problems and can share with friends), then they can request a refund.