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

The Internet of Things refers to a network of interconnected devices, sensors, and objects that can collect and exchange data. IoT Devices enable the…
Human-in-the-loop refers to a collaborative approach where humans and AI systems work together to achieve optimal results. It involves combining human expertise, judgement, and…
Decision Trees are Machine Learning models that use a branching structure to make decisions or predictions. By determining the most important features and creating…