Introduction to Algorithms for Data Mining and Machine Learning
Yang, Xin-She
- 出版商: Academic Press
- 出版日期: 2019-06-19
- 售價: $2,850
- 貴賓價: 9.5 折 $2,708
- 語言: 英文
- 頁數: 188
- 裝訂: Quality Paper - also called trade paper
- ISBN: 0128172169
- ISBN-13: 9780128172162
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相關分類:
Machine Learning、Algorithms-data-structures、Data-mining
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相關主題
商品描述
Introduction to Algorithms for Data Mining and Machine Learning introduces the essential ideas behind all key algorithms and techniques for data mining and machine learning, along with optimization techniques. Its strong formal mathematical approach, well selected examples, and practical software recommendations help readers develop confidence in their data modeling skills so they can process and interpret data for classification, clustering, curve-fitting and predictions. Masterfully balancing theory and practice, it is especially useful for those who need relevant, well explained, but not rigorous (proofs based) background theory and clear guidelines for working with big data.
- Presents an informal, theorem-free approach with concise, compact coverage of all fundamental topics
- Includes worked examples that help users increase confidence in their understanding of key algorithms, thus encouraging self-study
- Provides algorithms and techniques that can be implemented in any programming language, with each chapter including notes about relevant software packages
商品描述(中文翻譯)
《資料探勘與機器學習演算法入門》介紹了資料探勘和機器學習的所有關鍵演算法和技術的基本概念,以及優化技術。它採用強調形式化數學方法、選擇性的範例和實用的軟體建議,幫助讀者建立對於資料建模技能的信心,以便進行分類、分群、曲線擬合和預測等數據處理和解釋。這本書巧妙地平衡了理論和實踐,對於那些需要相關、易於理解但不需要嚴謹(基於證明的)背景理論和處理大數據的明確指南的人尤其有用。
該書以非正式、無定理的方式呈現,簡潔而全面地涵蓋了所有基本主題。它包含了幫助讀者增加對關鍵演算法理解的實例,從而鼓勵自學。書中提供了可以在任何程式語言中實現的演算法和技術,每章還包括有關相關軟體套件的註解。