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

Reinforcement Learning is a branch of AI that focuses on training agents to make decisions through trial and error in a specific environment. By…
Deep Learning, a subfield of AI, leverages neural networks with numerous interconnected layers to process vast amounts of data, enabling machines to learn and…
The Internet of Things refers to a network of interconnected devices, sensors, and objects that can collect and exchange data. IoT Devices enable the…
The Viterbi Algorithm is a dynamic programming algorithm used in sequence analysis, such as speech recognition and Natural Language Processing. It finds the most…