Scikit-Learn API
The objective of the scikit-learn API is to provide an efficient and unified syntax to make ML accessible to non-ML experts, as well as to facilitate and popularize its use among several industries.
How Does It Work?
Although it has many collaborators, the scikit-learn API was built and has been updated by considering a set of principles that prevent framework code proliferation, where different code performs similar functionalities. On the contrary, it promotes simple conventions and consistency. Due to this, the scikit-learn API is consistent among all models, and once the main functionalities have been learned, it can be used widely.
The scikit-learn API is divided into three complementary interfaces that share a common syntax and logic: the estimator, the predictor, and the transformer. The estimator interface is used for creating models and fitting the data into them; the predictor, as its name suggests, is used to make predictions based on the models...
