Features/ attributes/ features: features or attributes are the individual measurements that, when combined with other features, make up a training example.
Instance: made up of features
Training set: the set of training examples we’ll use to train our machine learning algorithms.
Target variable: what we’ll be trying to predict with our machine learning algorithms.
Knowledge representation, what the machine has learned. May be in the form of a set of rules; it may be a probability distribution or an example from the training set.