Machine Learning: Unsupervised and Supervised Learning

Course description

Supervised and unsupervised machine learning, also known as classification and clustering, are important statistical techniques commonly applied in many social and behavioral science research problems. Both seek to understand social phenomena through the identification of naturally occurring homogeneous groupings within a population. Supervised learning techniques are used to sort new observations into pre- existing or known groupings, while unsupervised learning techniques sort the population under study into natural, homogeneous groupings based on their observed characteristics. Both help to reveal hidden structure that may be used in further analyses. This course will compare and contrast these techniques, including many of their variations, with an emphasis on applications.