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

Ethics in AI focuses on the responsible and ethical use of AI technologies. Businesses must consider the fairness, transparency, accountability, and privacy implications of…
istributed Computing refers to the use of multiple computers or servers to perform computational tasks in a networked environment. It enables businesses to process…
Reinforcement Learning is a branch of AI that focuses on training agents to make decisions through trial and error in a specific environment. By…
Robotics involves designing, building, and programming machines that can perform tasks autonomously or interact with humans. By combining AI with physical systems, businesses can…