The fundamental idea behind machine learning is that flexible and automatic methods are utilised to find patterns in the data, with a particular emphasis on forecasting future data. The specifics of the approaches are not as crucial as the broader concepts that might be used in virtually every ML scenario and, in fact, many conventional procedures as well. Although there will be examples utilising the R statistical environment and discussions of a few particular meth­ods, the emphasis here is more on concepts than application and is maintained as much as possible at the conceptual level. These model examples are also accessible in Python.

Book Information: