Learning with Kernels 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2025

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Bernhard Schlkopf 作者

The MIT Press

译者

2001-12-15 出版日期

648 页数

USD 79.00 价格

Hardcover

Adaptive Computation and Machine Learning 丛书系列

9780262194754 图书编码

Learning with Kernels 在线电子书图书标签: 机器学习核方法 MachineLearning Kernels 支持向量机与核方法 kernel 数学支持向量机

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发表于2025-03-03

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Learning with Kernels 在线电子书 epub 下载 mobi 下载 pdf 下载 txt 下载 2025

Learning with Kernels 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2025

Learning with Kernels 在线电子书用户评价

评分☆☆☆☆☆

我觉得这本书的最大优势就是里面的notation都是数学家惯用的，看着太顺眼！再看看它的邻居TESL，里面的notation简直了！

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Everything about kernels, based on Smola's PhD thesis

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比SLT写的易懂

评分☆☆☆☆☆

我觉得这本书的最大优势就是里面的notation都是数学家惯用的，看着太顺眼！再看看它的邻居TESL，里面的notation简直了！

评分☆☆☆☆☆

Everything about kernels, based on Smola's PhD thesis

Learning with Kernels 在线电子书著者简介

Learning with Kernels 在线电子书图书目录

Learning with Kernels 在线电子书 pdf 下载 txt下载 epub 下载 mobi 在线电子书下载

Learning with Kernels 在线电子书图书描述

In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs -- -kernels--for a number of learning tasks. Kernel machines provide a modular framework that can be adapted to different tasks and domains by the choice of the kernel function and the base algorithm. They are replacing neural networks in a variety of fields, including engineering, information retrieval, and bioinformatics.Learning with Kernels provides an introduction to SVMs and related kernel methods. Although the book begins with the basics, it also includes the latest research. It provides all of the concepts necessary to enable a reader equipped with some basic mathematical knowledge to enter the world of machine learning using theoretically well-founded yet easy-to-use kernel algorithms and to understand and apply the powerful algorithms that have been developed over the last few years.

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Learning with Kernels 在线电子书读后感

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It is an excellent book about learning with kernels. Another issue related to kernels is learning kernels, not learning with kernels. Kernel learning has a long history in research and is important in SVM because it has pretty theoretical properties.

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This book is a good introductory material for kernel-based machine learning tools. The first part provides an reviews on the required mathematic tools in decision theory (risk and lost functions), statical learning theory and optimization theory. I strongly...

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Learning with Kernels 在线电子书 pdf 下载 txt下载 epub 下载 mobi 下载 2025