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

Bayesian networks are Probabilistic Graphical Models that represent and evaluate uncertainty and conditional dependencies between variables. Industries such as healthcare and finance use Bayesian…
Data Science encompasses the collection, analysis, interpretation, and visualisation of data to extract valuable insights and make informed decisions. It combines statistical techniques, Machine…
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…
Hyperparameters are parameters that are set before the training of an AI model. They control the behaviour and performance of the model, such as…