Statistical Machine Learning: From Theory to Practice

Catalog description

Explores the design, analysis and construction of algorithms that can learn from data and make inferences or predictions about future outcomes. Covers the theory and practice of machine learning (ML) focusing on a methodical approach that highlights the role of statistical and computational methods in analysis of data. Includes a near equal dose of theory and practice with the goal of providing a thorough grounding in the fundamental methodologies and algorithms in machine learning.