What is Support Vector Machines?

Skill Level:

Support Vector Machines (SVMs) are Machine Learning algorithms used for classification and regression tasks. SVMs create decision boundaries and maximise the margin between different classes of data. Businesses leverage SVMs for tasks like image classification, text categorisation, and time series analysis.

Other Definitions

Feature Extraction refers to the process of identifying and selecting the most relevant features from raw data to enhance AI model performance. By extracting…
Incremental Learning is an AI technique that allows models to continuously learn from new data without retraining from scratch. Instead of training the model…
Quantum Computing and AI are two fields that can complement and enhance each other. Quantum Computing can perform calculations faster and more efficiently than…
Ensemble Learning involves combining multiple Machine Learning models to achieve superior performance and accuracy. By leveraging the “wisdom of the crowd,” Ensemble Learning mitigates…