A Gentle Introduction to Autoencoders & Latent Space

This article introduces autoencoders and latent space as a method for compressing high-dimensional data into lower-dimensional representations while preserving key information. It explains how this technique helps mitigate computational challenges in machine learning, particularly in generative AI applications. The post serves as a beginner-friendly overview of these concepts.