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Image Denoising Using AutoEncoders in Keras and Python
  • Level Professional
  • المدة 3 ساعات hours
  • Offered by

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In this 1-hour long project-based course, you will be able to: - Understand the theory and intuition behind Autoencoders - Import Key libraries, dataset and visualize images - Perform image normalization, pre-processing, and add random noise to images - Build an Autoencoder using Keras with Tensorflow 2.0 as a backend - Compile and fit Autoencoder model to training data - Assess the performance of trained Autoencoder using various KPIs 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.

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Explore the fascinating world of image denoising with the "Image Denoising Using AutoEncoders in Keras and Python" course. Ideal for intermediate learners in IT & Computer Science, this 1-hour project-based course, offered by Coursera, covers the theory behind Autoencoders, image normalization, pre-processing, and building an Autoencoder using Keras with Tensorflow 2. Enjoy a hands-on learning experience with free access to this engaging content.