Training set, in the context of artificial intelligence and machine learning, refers to a data set that is used to train a machine learning model or algorithm.
The training set consists of a set of labelled examples, where each example includes features (also known as independent variables or predictors) and a label (also known as a dependent or target variable). The machine learning model uses the training set to learn to relate input features to output labels, so that it can generalise to predict output labels for new examples.
The training set is a critical component of the machine learning process, as the quality and quantity of the training data influences the accuracy of the resulting model.
In the dynamic financial world, optimizing the return on available assets is essential to the success of any lender. Gam [...]
Read More »To know how semantic technology works, the first thing you need to know is that it is responsible for helping artificial intelligence systems [...]
Read More »As a consequence of this pandemic and economic situation in which we have found ourselves for the last two years, with the intention of better protecting the [...]
Read More »The term artificial intelligence (AI) is nowadays, but it was invented in 1956 by John McCarthy, Marvin Minsky and Claude Shannon in the famous [...]
Read More »
