Introducing Variational Autoencoders (in Prose and Code)

Effective machine learning means building expressive models that sift out signal from noise—that simplify the complexity of real-world data, yet accurately intuit and capture its subtle underlying patterns. Whatever the downstream application, a primary challenge often boils down to this: How do we represent, or even synthesize, complex data in the context of a tractable model? This challenge is c