Image Denoising Using AutoEncoders in Keras and Python

This 1-hour-long project-based course will teach you how to: – Understand the theory and intuition behind Autoencoders; – Import Key libraries, data and visualize images; - Perform image normalization, post-processing and add random noise to images; - Build an Autoencoder with Keras with Tensorflow2.0 as a backend; - Compile and fit Autoencoder models to training data; - Evaluate the performance of trained Autoencoders using various KPIs We are currently working to offer the same experience in other areas.