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

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…
Synthetic Data is artificially generated data that mimics real-world data. Synthetic data can be used to train Machine Learning models when real data is…
Autonomous agents are AI systems that can perform actions and make decisions independently, guided by predefined goals or learning processes. Businesses leverage autonomous agents…
The Viterbi Algorithm is a dynamic programming algorithm used in sequence analysis, such as speech recognition and Natural Language Processing. It finds the most…