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

ChatGPT is an AI model developed by OpenAI that excels in generating human-like text-based responses. Powered by advanced language models and deep learning techniques,…
Pattern Recognition is an AI technique that recognises patterns and structures in data. This approach involves identifying common features or characteristics and using these…
Forecasting involves predicting future outcomes or trends based on historical data and patterns. By analysing past data and applying statistical techniques, businesses can make…
Expert Systems are AI systems that emulate human expertise in specific domains. By capturing and codifying human knowledge, Expert Systems assist businesses in decision-making,…