Machine Learning: The Art and Science of Algorithms that Make Sense of Data (Paperback)

Peter Flach



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.


作為最全面的機器學習教材之一,這本書充分展現了這個領域的豐富性,同時也不忘記統一原則。彼得·弗拉赫(Peter Flach)清晰而以實例為基礎的方法首先討論了垃圾郵件過濾器的工作原理,這立即介紹了機器學習的實際應用,並且技術上的繁瑣最少。弗拉赫提供了越來越複雜和多樣化的案例研究,並且選擇了精心挑選的例子和插圖。他涵蓋了各種邏輯、幾何和統計模型,以及矩陣分解和ROC分析等最新話題。特別關注的是特徵的核心作用。使用已確立的術語與引入新的有用概念相平衡,並提供相關背景材料的摘要,如果需要,還提供了復習的指引。這些特點確保了《機器學習》將成為一本新的標準入門教材。