Basics of Autoencoders
Explore the fundamentals of autoencoders and how they learn to reconstruct input data through encoding and decoding. Understand their structure, including the latent space representation, and see practical applications such as data compression, denoising, and anomaly detection. Gain hands-on experience by replicating a convolutional autoencoder model using PyTorch, enhancing your knowledge of deep learning architectures.
We'll cover the following...
We'll cover the following...
Before we discuss variational autoencoders, let’s first see how the standard autoencoders work.
Autoencoders are simple neural networks such that their output is their input.
It is as simple as that.
Their goal is to ...