My Account
Forward Thinking Logo

What is Multimodal Learning?

Skill Level:

Multi-Modal learning refers to AI models that learn from multiple sources of data, such as text, images, and audio. By incorporating information from multiple modalities, these models can capture richer and more comprehensive representations. Multimodal Learning finds applications in areas like sentiment analysis, image captioning, and video understanding.

Other Definitions

Data Preprocessing

Data Preprocessing involves preparing and cleaning raw data before analysis. By removing noise, selecting relevant features, and addressing missing values, businesses can ensure data…

Federated Learning

Federated Learning is a privacy-preserving technique where AI models are trained across multiple decentralised devices or systems without sharing raw data. Instead, only aggregated…

Unsupervised Learning

Unsupervised Learning is a Machine Learning technique where models learn patterns and structures within data without labelled examples. By uncovering hidden relationships and clustering…

Sentiment Analysis

Sentiment Analysis is an AI technique that analyses emotions and opinions expressed in text data. Sentiment analysis can classify text as positive, negative, or…
Back to Glossary