Unsupervised Machine Learning for Clustering in Political and Social Research

Discover the essential guide for researchers and educators in "Unsupervised Machine Learning for Clustering in Political and Social Research" by Philip D. Waggoner. Published in 2021, this insightful book spans 75 pages and provides a comprehensive introduction to clustering, a key component of unsupervised machine learning. Waggoner expertly explores how clustering can reveal hidden, non-random structures within data, making it an invaluable resource for those in the social sciences. The book covers a variety of widely used clustering techniques, complemented by R code and real-world data examples to enhance your understanding and application of these concepts. Whether you're a seasoned researcher or a curious learner, this book is designed to facilitate your journey into the world of data analysis and clustering techniques.