Hockey - Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning series)

Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning series)

Name: Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning series)
Price: 80.00 USD
Availability: InStock
Rating: 4.5 (30 reviews)

4.5 of 5 Stars: Hockey - Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning series)

$80.00

Buying Options

Description

Book Synopsis:

A comprehensive introduction to Support Vector Machines and related kernel methods.

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.

Details

Are you looking to enhance your knowledge in machine learning and stay ahead of the competition? Look no further than "Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond"! This comprehensive book, part of the Adaptive Computation and Machine Learning series, introduces you to the world of Support Vector Machines (SVM) and kernel methods. With results derived from statistical learning theory, SVMs have revolutionized the field of machine learning.

One of the key advantages of SVMs is their modular framework, allowing them to be adapted to different tasks and domains. By selecting the appropriate kernel function and algorithm, you can unlock the full potential of these learning machines. As a result, they are rapidly replacing neural networks in various industries, including engineering, information retrieval, and bioinformatics.

Whether you are a beginner or an experienced practitioner, "Learning with Kernels" caters to your needs. Starting from the basics, the book gradually dives into advanced topics and the latest research. Don't worry if you only have basic mathematical knowledge; this book equips you with the necessary concepts to confidently venture into the world of machine learning. From easy-to-use kernel algorithms to powerful techniques developed in recent years, you'll gain a deep understanding of SVMs and their applications.

Don't miss out on this opportunity to level up your skills and gain a competitive edge! Grab your copy of "Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond" now by clicking here. Start your journey towards mastering machine learning today!

See All Buying Options...

More Details...