This textbook provides a solid mathematical basis for understanding popular data science algorithms for clustering and classification and shows that an in-depth understanding of the mathematics powering these algorithms gives insight into the underlying data. It presents a step-by-step derivation of these algorithms, outlining their implementation from scratch in a computationally sound way.
Mathematics of Data Science: A Computational Approach to Clustering and Classification
"Sinopsis" puede pertenecer a otra edición de este libro.
Daniela Calvetti is the James Wood Williamson Professor in the Department of Mathematics, Applied Mathematics, and Statistics at Case Western Reserve University. Her research interests, strongly rooted in numerical analysis, include inverse problems, uncertainty quantification, and mathematical modeling, with a specific focus on human metabolism and the brain. She is a member of SIAM and the International Society for Cerebral Blood Flow and Metabolism.
Erkki Somersalo is a professor in the Department of Mathematics, Applied Mathematics, and Statistics at Case Western Reserve University, with a background in analysis and partial differential equations. His research interests include computational inverse problems, with an emphasis on Bayesian methods, and applications to a wide range of areas, particularly to medical imaging. He is a founding member of the Finnish Inverse Problems Society and a member of the Finnish Academy of Sciences and Letters and SIAM. He is also a fellow of the Institute of Physics, UK.
"Sobre este título" puede pertenecer a otra edición de este libro.
Librería: Brook Bookstore On Demand, Napoli, NA, Italia
Condición: new. Nº de ref. del artículo: PLV1SVHSMS
Cantidad disponible: 4 disponibles
Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
Condición: New. 2021. Paperback. . . . . . Nº de ref. del artículo: V9781611976366
Cantidad disponible: 1 disponibles
Librería: Revaluation Books, Exeter, Reino Unido
Paperback / Softback. Condición: Brand New. 189 pages. 10.94x8.43x0.91 inches. In Stock. Nº de ref. del artículo: __1611976367
Cantidad disponible: 2 disponibles
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: FW-9781611976366
Cantidad disponible: 4 disponibles
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
Paperback. Condición: New. This textbook provides a solid mathematical basis for understanding popular data science algorithms for clustering and classification and shows that an in-depth understanding of the mathematics powering these algorithms gives insight into the underlying data. It presents a step-by-step derivation of these algorithms, outlining their implementation from scratch in a computationally sound way.Mathematics of Data Science: A Computational Approach to Clustering and Classificationproposes different ways of visualizing high-dimensional data to unveil hidden internal structures, andincludes graphical explanations and computed examples using publicly available data sets in nearly every chapter to highlight similarities and differences among the algorithms. Nº de ref. del artículo: LU-9781611976366
Cantidad disponible: 2 disponibles
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
Condición: New. Nº de ref. del artículo: 42283997-n
Cantidad disponible: 4 disponibles
Librería: Majestic Books, Hounslow, Reino Unido
Condición: New. Nº de ref. del artículo: 401048282
Cantidad disponible: 3 disponibles
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
Condición: As New. Unread book in perfect condition. Nº de ref. del artículo: 42283997
Cantidad disponible: 4 disponibles
Librería: Kennys Bookstore, Olney, MD, Estados Unidos de America
Condición: New. 2021. Paperback. . . . . . Books ship from the US and Ireland. Nº de ref. del artículo: V9781611976366
Cantidad disponible: 1 disponibles
Librería: Books Puddle, New York, NY, Estados Unidos de America
Condición: New. Nº de ref. del artículo: 26395328773
Cantidad disponible: 3 disponibles