What is Variational Autoencoders (VAE)?

Skill Level:

Variational Autoencoders are a type of generative model used in unsupervised learning. VAEs learn a low-dimensional representation of input data and can generate new data samples similar to the training data. They have applications in tasks such as image generation, anomaly detection, and data compression.

Other Definitions

Zero-Shot Learning is an AI approach that enables models to learn to recognise new classes or concepts without explicit training examples. This is achieved…
Machine Learning is a powerful branch of Artificial Intelligence (AI) that focuses on enabling computer systems to learn and improve from experience without being…
Reinforcement Learning is a branch of AI that focuses on training agents to make decisions through trial and error in a specific environment. By…
ChatGPT is an AI model developed by OpenAI that excels in generating human-like text-based responses. Powered by advanced language models and deep learning techniques,…