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Introduction to Machine Learning: Illustrated Principles.
・ISBN 978-1-009-67270-2 paper GB£ 30.00
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お気に入り
★★★
| 著者・編者 | Shelton, Christian R., |
|---|---|
| 出版社 | (Cambridge University Press, UK) |
| 出版年月 | 2026 |
| ページ数 | 300 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A05-74660＞ |
解説
Aimed at undergraduate students, this text guides readers through the methods and principles of machine learning in an approachable manner without sacrificing mathematical precision or notation. Step-by-step explanations allow students to grasp complicated mathematical calculations and translate the theory and mathematics into programming and applications. The text presents machine learning concepts visually, and uses example datasets from fictional hippopotamuses and illustrations to explain the material in a unique, but easily understood and engaging way. Worked examples connect the mathematics and algorithms to real-world applications and enable students to utilize this technology in new and ever-changing circumstances. Topics covered include Bayesian reasoning, linear regression and classification, margin-based classification, cross-validation, neural networks, decision trees, clustering and dimensionality reduction. End-of-chapter mathematical exercises and additional coding projects reinforce application and decision-making skills.