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Essential reading for students and practitioners, this book focuses on practical algorithms used to solve key problems in data mining, with exercises suitable for students from the advanced undergraduate level and beyond. This second edition includes new and extended coverage on social networks, machine learning and dimensionality reduction.

Produktbeschreibung
Essential reading for students and practitioners, this book focuses on practical algorithms used to solve key problems in data mining, with exercises suitable for students from the advanced undergraduate level and beyond. This second edition includes new and extended coverage on social networks, machine learning and dimensionality reduction.
Autorenporträt
Timothy Hellwig is an Associate Professor of Political Science and the Director of the Institute for European Studies at Indiana University, Bloomington. His work has been published in several peer-reviewed journals, including the American Journal of Political Science, the British Journal of Political Science, Comparative Political Studies, and the Journal of Politics. He has previously served as a researcher at the International Foundation for Election Systems, with the faculty at the University of Houston, and as a visiting researcher at the University of Essex and at Gothenburg University.