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Könyv Kernel Methods for Machine Learning with Math and R Joe Suzuki

Kernel Methods for Machine Learning with Math and R

100 Exercises for Building Logic

Szerző: Joe Suzuki
Nyelv: Angol
Kötés: Puha kötésű
Kiadó: Springer Verlag, Singapore
Elérhetőség: Beszállítói készleten
Küldés 5-8 napon belül
15 991 Ft
The most crucial ability for machine learning and data science is mathematical logic for grasping th...

Információk a könyvről

Szerző
Joe Suzuki
Nyelv
Angol
Kötés
Könyv - Puha kötésű
Kiadva
2022
oldal
196
EAN
9789811903977
Enbook ID
38637044
Kiadó
Springer Verlag, Singapore
Súly
326
Méretek
155 x 235 x 12

Teljes leírás

The most crucial ability for machine learning and data science is mathematical logic for grasping their essence rather than relying on knowledge or experience. This textbook addresses the fundamentals of kernel methods for machine learning by considering relevant math problems and building R programs. The book's main features are as follows:The content is written in an easy-to-follow and self-contained style.The book includes 100 exercises, which have been carefully selected and refined. As their solutions are provided in the main text, readers can solve all of the exercises by reading the book.The mathematical premises of kernels are proven and the correct conclusions are provided, helping readers to understand the nature of kernels.Source programs and running examples are presented to help readers acquire a deeper understanding of the mathematics used.Once readers have a basic understanding of the functional analysis topics covered in Chapter 2, the applications are discussed in the subsequent chapters. Here, no prior knowledge of mathematics is assumed.This book considers both the kernel for reproducing kernel Hilbert space (RKHS) and the kernel for the Gaussian process; a clear distinction is made between the two.

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