"A subset of data science, falling at the intersection of traditional statistics and machine learning. Machine learning refers to the construction and study of computer
algorithms — step-by-step procedures used for calculations and classification — that can ‘learn’
when exposed to new data. This enables better predictions and decisions to be made based on what
was experienced in the past, as with filtering spam emails, for example. The addition of “statistical”
reflects the emphasis on statistical analysis and methodology, which is the main approach to modern
machine learning."

Source: Data-Pop Alliance (2015). Beyond Data Literacy: Reinventing Community Engagement and Empowerment in the Age of Data.” Data-Pop Alliance White Paper Series. Data-Pop Alliance (Harvard Humanitarian
Initiative, MIT Media Lab and Overseas Development Institute) and Internews. September 2015.

Download: https://dspace.mit.edu/handle/1721.1/123471