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- Level Professional
- المدة 3 ساعات hours
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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.Auto Summary
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.