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Fundamentals of Probability and Statistics for Machine Learning
Not yet published
Expected 2 Dec 25An introductory textbook for undergraduate or beginning graduate students that integrates probability and statistics with their applications in machine learning.
Most curricula have students take an undergraduate course on probability and statistics before turning to machine learning. In this innovative textbook, Ethem Alpaydın offers an alternative tack by integrating these subjects for a first course on learning from data. Alpaydın accessibly connects machine learning to its roots in probability and statistics, starting with the basics of random experiments and probabilities and eventually moving to complex topics such as artificial neural networks. With a practical emphasis and learn-by-doing approach, this unique text offers comprehensive coverage of the elements fundamental to an empirical understanding of machine learning in a data science context.
Consolidates foundational knowledge and key techniques needed for modern data scienceEmphasizes hands-on learningCovers mathematical fundamentals of probability and statistics and ML basicsSuits undergraduates as well as self-learners with basic programming experienceIncludes slides, solutions, and code
Most curricula have students take an undergraduate course on probability and statistics before turning to machine learning. In this innovative textbook, Ethem Alpaydın offers an alternative tack by integrating these subjects for a first course on learning from data. Alpaydın accessibly connects machine learning to its roots in probability and statistics, starting with the basics of random experiments and probabilities and eventually moving to complex topics such as artificial neural networks. With a practical emphasis and learn-by-doing approach, this unique text offers comprehensive coverage of the elements fundamental to an empirical understanding of machine learning in a data science context.
Consolidates foundational knowledge and key techniques needed for modern data scienceEmphasizes hands-on learningCovers mathematical fundamentals of probability and statistics and ML basicsSuits undergraduates as well as self-learners with basic programming experienceIncludes slides, solutions, and code
560 pages, Hardcover
Expected publication December 2, 2025
About the author
Ethem Alpaydin
7Ìýbooks14ÌýfollowersEthem ALPAYDIN received his BSc from Department of Computer Engineering of Bogazici University in 1987 and the degree of Docteur es Sciences from Ecole Polytechnique Fédérale de Lausanne in 1990. He did his postdoctoral work at the International Computer Science Institute, Berkeley in 1991 and afterwards was appointed Assistant Professor at the Department of Computer Engineering of Bogazici University. He was appointed Associate Professor in 1996 and Professor in 2002 in the same department.
As visiting researcher, he worked at Department of Brain and Cognitive Sciences, MIT in 1994, International Computer Science Institute, Berkeley in 1997, IDIAP, Switzerland in 1998, and TU Delft in 2014.
He was Fulbright Senior Scholar in 1997/1998 and received the Research Excellence Award from the Bogazici University Foundation in 1998 (junior faculty) and 2008 (senior faculty), the Young Scientist Award from the Turkish Academy of Sciences in 2001 and the Scientific Encouragement Award from the Turkish Scientific and Technical Research Council in 2002.
His book Introduction to Machine Learning was published by The MIT Press in October 2004; its German edition was published by Oldenbourg Verlag in May 2008, and Chinese edition was published by Huazhang Press in June 2009. Introduction to Machine Learning, second edition was published by The MIT Press in February 2010; its Turkish edition was published by Bogazici University Press in April 2011 and Chinese edition was published by Huazhang Press in June 2014. Introduction to Machine Learning, third edition was published by The MIT Press in August 2014.
He was an Editorial Board Member of The Computer Journal (Oxford University Press) in 2008-2014. He is a Member of The Science Academy, Turkey, Senior Member of the IEEE, and an Editorial Board Member of Pattern Recognition (Elsevier).
As visiting researcher, he worked at Department of Brain and Cognitive Sciences, MIT in 1994, International Computer Science Institute, Berkeley in 1997, IDIAP, Switzerland in 1998, and TU Delft in 2014.
He was Fulbright Senior Scholar in 1997/1998 and received the Research Excellence Award from the Bogazici University Foundation in 1998 (junior faculty) and 2008 (senior faculty), the Young Scientist Award from the Turkish Academy of Sciences in 2001 and the Scientific Encouragement Award from the Turkish Scientific and Technical Research Council in 2002.
His book Introduction to Machine Learning was published by The MIT Press in October 2004; its German edition was published by Oldenbourg Verlag in May 2008, and Chinese edition was published by Huazhang Press in June 2009. Introduction to Machine Learning, second edition was published by The MIT Press in February 2010; its Turkish edition was published by Bogazici University Press in April 2011 and Chinese edition was published by Huazhang Press in June 2014. Introduction to Machine Learning, third edition was published by The MIT Press in August 2014.
He was an Editorial Board Member of The Computer Journal (Oxford University Press) in 2008-2014. He is a Member of The Science Academy, Turkey, Senior Member of the IEEE, and an Editorial Board Member of Pattern Recognition (Elsevier).
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