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

Intelligent Virtual Assistants, also known as Chatbots or Virtual Agents, are AI-powered software applications that can engage in conversations and perform tasks on behalf…
Object Recognition is the capability of AI systems to identify and classify objects within images or videos. By utilising advanced algorithms and Neural Networks,…
Cognitive Computing involves creating computer systems that can imitate human cognitive abilities, such as perception, reasoning, learning, and problem-solving. By combining AI, Machine Learning,…
Hyperparameters are parameters that are set before the training of an AI model. They control the behaviour and performance of the model, such as…