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In this video on Variational Autoencoders (VAEs), we will dive into this fascinating deep learning model that combines elements of autoencoders and probabilistic graphical models. VAEs are a type of generative model, meaning they can generate new data points similar to the data they were trained on. The main idea behind a VAE is to learn a compact, continuous latent space representation of the input data, making it possible to sample and generate new data points that resemble the original input distribution.

00: 00 Introduction
02: 15 What is Variational Autoencoder ?
05: 30 Building the model architecture
15: 20 Test the model with Inference

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