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学生对 Coursera Project Network 提供的 Image Super Resolution Using Autoencoders in Keras 的评价和反馈

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Welcome to this 1.5 hours long hands-on project on Image Super Resolution using Autoencoders in Keras. In this project, you’re going to learn what an autoencoder is, use Keras with Tensorflow as its backend to train your own autoencoder, and use this deep learning powered autoencoder to significantly enhance the quality of images. That is, our neural network will create high-resolution images from low-res source images. 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 Keras pre-installed. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - 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....



Jun 16, 2020

Very informative, but extremely short project, I would have loved for more explanation on the theory behind each of the layers used and more loss functions and optimizer.


May 27, 2020

Amazing course to gain knowledge in one of the trending field i.e. Image Super Resolution. I gain what I was looking for in this particular guided project.


1 - Image Super Resolution Using Autoencoders in Keras 的 25 个评论(共 56 个)

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