MACHINE LEARNING. SUPERVISED LEARNING THROUGH R. SCIKIT LEARN

The goal of supervised machine learning is to build a model that makes evidence-based predictions in the presence of uncertainty.

A supervised learning algorithm takes a known set of input data and known responses to the data (output) and trains a model to generate reasonable predictions for the response to new data.

Supervised learning uses classification and regression techniques to develop predictive models.

Learning techniques are developed and illustrated with fully solved examples from the appropriate software for it.

The R language and its related Machine Learning libraries will be used , ideal for working in this field.