| 書目名稱 | Principles of Machine Learning | | 副標(biāo)題 | The Three Perspectiv | | 編輯 | Wenmin Wang | | 視頻video | http://file.papertrans.cn/765/764495/764495.mp4 | | 概述 | Proposing the three perspectives with their logical and hierarchical relationships to machine learning.Elaborating the historical context, theoretical foundations, and development processes of machine | | 圖書封面 |  | | 描述 | .Conducting an in-depth analysis of machine learning, this book proposes three perspectives for studying machine learning: the learning frameworks, learning paradigms, and learning tasks. With this categorization, the learning frameworks reside within the theoretical perspective, the learning paradigms pertain to the methodological perspective, and the learning tasks are situated within the problematic perspective. Throughout the book, a systematic explication of machine learning principles from these three perspectives is provided, interspersed with some examples...The book is structured into four parts, encompassing a total of fifteen chapters. The inaugural part, titled “Perspectives,” comprises two chapters: an introductory exposition and an exploration of the conceptual foundations. The second part, “Frameworks”: subdivided into five chapters, each dedicated to the discussion of five seminal frameworks: probability, statistics, connectionism, symbolism, and behaviorism. Continuing further, the third part, “Paradigms,” encompasses four chapters that explain the three paradigms of supervised learning, unsupervised learning, and reinforcement learning, and narrating several quasi | | 出版日期 | Textbook 2025 | | 關(guān)鍵詞 | machine learning; supervised learning; unsupervised learning; reinforcement learning; deep learning | | 版次 | 1 | | doi | https://doi.org/10.1007/978-981-97-5333-8 | | isbn_softcover | 978-981-97-5335-2 | | isbn_ebook | 978-981-97-5333-8 | | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor |
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