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

ChatOps combines chat platforms and AI technologies to facilitate collaboration and automate tasks within teams. By integrating AI-powered chatbots and communication tools, businesses can…
Cognitive Robotics involves the integration of AI and robotics to create intelligent machines that can interact and collaborate with humans in a human-like manner….
Decision networks, also known as Probabilistic Graphical Models, are a type of AI model that represents uncertain knowledge using a graph structure. Decision Networks…
Forecasting involves predicting future outcomes or trends based on historical data and patterns. By analysing past data and applying statistical techniques, businesses can make…