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Volver a Image Noise Reduction with Auto-encoders using TensorFlow

Opiniones y comentarios de aprendices correspondientes a Image Noise Reduction with Auto-encoders using TensorFlow por parte de Coursera Project Network

4.7
estrellas
105 calificaciones
15 reseña

Acerca del 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....

Principales reseñas

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 revisiones para 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 oct. 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 feb. 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.