内容简介
As one of the most comprehensive machine learning texts around, this book does justice to the field's incredible richness, but without losing sight of the unifying principles. Peter Flach's clear, example-based approach begins by discussing how a spam filter works, which gives an immediate introduction to machine learning in action, with a minimum of technical fuss. Flach provides case studies of increasing complexity and variety with well-chosen examples and illustrations throughout. He covers a wide range of logical, geometric and statistical models and state-of-the-art topics such as matrix factorisation and ROC analysis. Particular attention is paid to the central role played by features. The use of established terminology is balanced with the introduction of new and useful concepts, and summaries of relevant background material are provided with pointers for revision if necessary. These features ensure Machine Learning will set a new standard as an introductory textbook.
作者简介
Peter Flach has more than twenty years of experience in machine learning teaching and research. He is Editor-in-Chief of Machine Learning and Program Co-Chair of the 2009 ACM Conference on Knowledge Discovery and Data Mining and the 2012 European Conference on Machine Learning and Data Mining. His research spans all aspects of machine learning, from knowledge representation and the use of logic to learn from highly structured data to the analysis and evaluation of machine learning models and methods to large-scale data mining. He is particularly known for his innovative use of Receiver Operating Characteristic (ROC) analysis for understanding and improving machine learning methods. These innovations have proved their effectiveness in a number of invited talks and tutorials and now form the backbone of this book.
精彩书评
"This textbook is clearly written and well organized. Starting from the basics, the author skillfully guides the reader through his learning process by providing useful facts and insight into the behavior of several machine learning techniques, as well as the high-level pseudocode of many key algorithms."
——Fernando Berzal, Computing Reviews
前言/序言
Machine Learning: The Art and Science of Algorithms that Make Sense of Data [平装] 下载 mobi epub pdf txt 电子书 格式
Machine Learning: The Art and Science of Algorithms that Make Sense of Data [平装] 下载 mobi pdf epub txt 电子书 格式 2024
评分
☆☆☆☆☆
如今,机器学习正在互联网上下掀起热潮,而Python则是非常适合开发机器学习系统的一门优秀语言。作为动态语言,它支持快速探索和实验,并且针对Python的机器学习算法库的数量也与日俱增。本书最大的特色,就是结合实例分析教会读者如何通过机器学习解决实际问题。
评分
☆☆☆☆☆
618囤货中,经济实惠。给力,期待明年
评分
☆☆☆☆☆
学习python中,很不错的书籍
评分
☆☆☆☆☆
一次买了很多书,就是看京东送货快捷方便,以后会经常光顾的。
评分
☆☆☆☆☆
这个类型的书还是很多,买了几本,内容上有互补,很好。
评分
☆☆☆☆☆
买了很久才来晒单,书里面好多代码,好好学
评分
☆☆☆☆☆
说的包装很完整,只是还没有打开看,应该还不错吧,这个系列的书买了很多
评分
☆☆☆☆☆
屯书进行时!!!特别不错,正版图书!!!
评分
☆☆☆☆☆
经典书籍,不用多说啦,很好满意(?ω?)hiahiahia
Machine Learning: The Art and Science of Algorithms that Make Sense of Data [平装] mobi epub pdf txt 电子书 格式下载 2024