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• Statistical Learning from a Regression Perspective by Richard A. Berk
• Dive into Deep Learning by Aston Zhang
• Patterns, Predictions, and Actions: Foundations of Machine Learning by Moritz Hardt
• Text as Data: A New Framework for Machine Learning and the Social Sciences by Justin Grimmer
• The acquisition of American sign language by deaf children by Marina McIntire
• Tangible, ASL Classifier Concepts/DVD by Windell Smith
• Regression for Categorical Data by Gerhard Tutz
• Foundations of Machine Learning by Mehryar Mohri
• Boosting: Foundations and Algorithms by Robert E. Schapire
• Concentration Inequalities and Model Selection Ecole d'Eté de Probabilités de Saint-Flour XXXIII - 2003 by Pascal Massart
• A Theory of Learning and Generalization: With Applications to Neural Networks and Control Systems by Mathukumalli Vidyasagar
• An Exaltation of Larks by James Lipton
• International Journal of American Linguistics 73 (2007) 4: 381-508
• Foundations of Genetic Algorithms 1991 (FOGA 1) (v. 1) by Gregory J. E. Rawlins
• A Probabilistic Theory of Pattern Recognition by Luc Devroye
• Kernel Methods for Pattern Analysis by John Shawe-Taylor
• Pattern Recognition and Neural Networks by Brian D. Ripley
• Neural Network Learning: Theoretical Foundations by Martin Anthony
• Classification and Regression Trees by Leo Breiman
• Bayesian Learning for Neural Networks by Radford M. Neal

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