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Вернуться к Image Noise Reduction with Auto-encoders using TensorFlow

Отзывы учащихся о курсе Image Noise Reduction with Auto-encoders using TensorFlow от партнера Coursera Project Network

4.7
звезд
Оценки: 102
Рецензии: 14

О курсе

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....

Лучшие рецензии

NL
7 апр. 2020 г.

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 авг. 2020 г.

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

Фильтр по:

1–14 из 14 отзывов о курсе Image Noise Reduction with Auto-encoders using TensorFlow

автор: Narendra L L

8 апр. 2020 г.

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

автор: Ravi P B

17 апр. 2020 г.

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

автор: noman s

16 авг. 2020 г.

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

автор: Kolawole E O

11 окт. 2020 г.

Teachable and Readable course.

Thanks so much!!

автор: SUGUNA M

19 нояб. 2020 г.

Good project based course

автор: Nilesh N

28 мар. 2020 г.

Crisp and useful!

автор: XAVIER S M

2 июня 2020 г.

Very Helpful !

автор: SUMIT Y

9 июля 2020 г.

Fine !!

автор: Kamlesh C

7 авг. 2020 г.

Thanks

автор: sarithanakkala

23 июня 2020 г.

Useful

автор: p s

23 июня 2020 г.

Super

автор: tale p

17 июня 2020 г.

good

автор: Rohit M

13 июня 2020 г.

NICE COURSE :-))

автор: NAIDU P S A

27 июня 2020 г.

nice