Multivariate Statistics and Machine Learning: An Introduction to Applied Data Science Using R and Python - Rilegato

Denis, Daniel J.

Rilegato

ISBN 10: 103245427X ISBN 13: 9781032454276

Casa editrice: Routledge, 2025

Riassunto

Multivariate Statistics and Machine Learning is a hands-on textbook providing an in-depth guide to multivariate statistics and select machine learning topics using R and Python software.

The book offers a theoretical orientation to the concepts required to introduce or review statistical and machine learning topics, and in addition to teaching the techniques, instructs readers on how to perform, implement, and interpret code and analyses in R and Python in multivariate, data science, and machine learning domains. For readers wishing for additional theory, numerous references throughout the textbook are provided where deeper and less “hands on” works can be pursued.

With its unique breadth of topics covering a wide range of modern quantitative techniques, user-friendliness, and quality of expository writing, Multivariate Statistics and Machine Learning will serve as a key and unifying introductory textbook for students in the social, natural, statistical, and computational sciences for years to come.

Su questo libro

Informazioni sull'autore

Daniel J. Denis, Ph.D., is Professor of Quantitative Psychology at the University of Montana, U.S.A, where he has taught applied statistics courses since 2004. He is author of Applied Univariate, Bivariate, and Multivariate Statistics and Applied Univariate, Bivariate, and Multivariate Statistics Using Python.

Dettagli dell'edizione

• Editore: Routledge
• Data di pubblicazione: 2025
• Lingua: Inglese
• ISBN 10: 103245427X
• ISBN 13: 9781032454276
• Rilegatura: Copertina rigida
• Numero edizione: 1
• Numero di pagine: 584
• Contatto del produttore: Taylor and Francis, GPSR Taylor and Francis; gpsr@taylorandfrancis.com; ; Taylor & Francis Verlag GmbH, Kaufingerstraße 24; München; 80331; Germania