Publisher: | Morgan & Claypool Publishers |

Series: | MIX , Learning |

Author: | Colin Campbell |

Edition: | 1 |

ISBN-10: | 1608456161 |

ISBN-13: | 9781608456161 |

Pages: | 100 |

Published: | Feb 15 2011 |

Posted: | Nov 19 2014 |

Language: | English |

Book format: | |

Book size: | 0.66 MB |

Support Vectors Machines have become a well established tool within machine learning. They work well in practice and have now been used across a wide range of applications from recognizing hand-written digits, to face identification, text categorisation, bioinformatics, and database marketing. In this book we give an introductory overview of this subject. We start with a simple Support Vector Machine for performing binary classification before considering multi-class classification and learning in the presence of noise. We show that this framework can be extended to many other scenarios such as prediction with real-valued outputs, novelty detection and the handling of complex output structures such as parse trees. Finally, we give an overview of the main types of kernels which are used in practice and how to learn and make predictions from multiple types of input data. Table of Contents: Support Vector Machines for Classification / Kernel-based Models / Learning with Kernels

Download Link:

Over 70 code examples to create vector graphics and data visualizations! Overview Create impressive vector graphics and data visualizations in your browser Add animation and interactivity to your web applications Work with native SVGs to create complex vector graphics Develop cross-browser vector graphics solutions In Detail Raphal is an exceptional library that makes drawing vector graphics in the browser straightforward. It boasts a large number of methods that facilitate drawing and animating graphics, allowing developers to create flexible, interactive web applications and data visualizations. Learning Raphal JS Vector Graphics takes you from being a complete vector graphics novice to an accomplished vector graphics developer. Packed with illus...

Learn how to use R to apply powerful machine learning methods and gain an insight into real-world applications Overview Harness the power of R for statistical computing and data science Use R to apply common machine learning algorithms with real-world applications Prepare, examine, and visualize data for analysis Understand how to choose between machine learning models Packed with clear instructions to explore, forecast, and classify data In Detail Machine learning, at its core, is concerned with transforming data into actionable knowledge. This fact makes machine learning well-suited to the present-day era of "big data" and "data science". Given the growing prominence of Ra cross-platform, zero-cost statistical programming envi...

Apply effective learning algorithms to real-world problems using scikit-learn About This BookDesign and troubleshoot machine learning systems for common tasks including regression, classification, and clusteringAcquaint yourself with popular machine learning algorithms, including decision trees, logistic regression, and support vector machinesA practical example-based guide to help you gain expertise in implementing and evaluating machine learning systems using scikit-learnWho This Book Is ForIf you are a software developer who wants to learn how machine learning models work and how to apply them effectively, this book is for you. Familiarity with machine learning fundamentals and Python will be helpful, but is not essential. In Detail This book exam...

2007 - 2018 © eBooks-IT.org