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

Artificial Neural Networks are computational models inspired by the human brain’s structure and function. They consist of interconnected nodes that process and transmit data,…
Feature Extraction refers to the process of identifying and selecting the most relevant features from raw data to enhance AI model performance. By extracting…
Support Vector Machines (SVMs) are Machine Learning algorithms used for classification and regression tasks. SVMs create decision boundaries and maximise the margin between different…
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…