The Pricing Tool
Machine learning and gradient boosting is the basis on which the pricing tool is built. Machine learning is a sub-field of computer science which has evolved from the study of pattern recognition and computational learning theory in artificial intelligence. In 1959, Arthur Samuel defined machine learning as a "Field of study that gives computers the ability to learn without being explicitly programmed".
Gradient boosting is a machine learning technique for regression and classification problems, which produces a prediction model in the form of an ensemble of weak prediction models, typically decision trees. It builds the model in a stage-wise fashion like other boosting methods do. It generalizes them by allowing optimization of an arbitrary differentiable loss function.
We have a team of Marketers, Developers, Actuaries and Data Scientists which are all based in South Africa. Our goal is to ensure that the public has better access to price information on cars and properties. This information will then assist the public in making better financial choices.