Discuss the advantages, disadvantages of Autoencoder

1-2 page introduction about machine learning Autoencoders (architecture, how does encoder, hidden layer and decoder part works, how they compress and decompress the data (how is the encoder reducing the dimensionality of input data), types of loss functions and when to use them, advantages, disadvantages of Autoencoders, where can they be used ) Variational autoencoders(their differences with standard autoencoders, architecture, vector of means Mu(μ), vector of standard deviations Sigma(σ) and Sample Layer (vector) explained, Kullback-Leibler divergence, use cases of generative models) Couple of mathematical formulas, but not to many