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商品描述
Master the art of machine learning and data science by diving into the essence of mathematical logic with this comprehensive textbook. This book focuses on the widely applicable information criterion (WAIC), also described as the Watanabe-Akaike information criterion, and the widely applicable Bayesian information criterion (WBIC), also described as the Watanabe Bayesian information criterion. This book expertly guides you through relevant mathematical problems while also providing hands-on experience with programming in R and Stan. Whether you're a data scientist looking to refine your model selection process or a researcher who wants to explore the latest developments in Bayesian statistics, this accessible guide will give you a firm grasp of Watanabe Bayesian Theory.
The key features of this indispensable book include:
- A clear and self-contained writing style, ensuring ease of understanding for readers at various levels of expertise.
- 100 carefully selected exercises accompanied by solutions in the main text, enabling readers to effectively gauge their progress and comprehension.
- A comprehensive guide to Sumio Watanabe's groundbreaking Bayes theory, demystifying a subject once considered too challenging even for seasoned statisticians.
- Detailed source programs and Stan codes that will enhance readers' grasp of the mathematical concepts presented.
- A streamlined approach to algebraic geometry topics in Chapter 6, making Bayes theory more accessible and less daunting.
Embark on your machine learning and data science journey with this essential textbook and unlock the full potential of WAIC and WBIC today!
商品描述(中文翻譯)
掌握機器學習和數據科學的藝術,深入數學邏輯的本質,這本全面的教科書將為您提供幫助。本書專注於廣泛適用的信息準則(WAIC),也稱為渡邊-赤池信息準則,以及廣泛適用的貝葉斯信息準則(WBIC),也稱為渡邊貝葉斯信息準則。本書專業地引導您解決相關的數學問題,同時提供使用 R 和 Stan 編程的實踐經驗。無論您是希望完善模型選擇過程的數據科學家,還是想探索貝葉斯統計最新發展的研究人員,這本易於理解的指南將使您對渡邊貝葉斯理論有堅實的掌握。
這本不可或缺的書籍的主要特點包括:
1. 清晰且自成體系的寫作風格,確保各個專業水平的讀者都能輕鬆理解。
2. 100 道精心挑選的練習題,並在正文中附有解答,使讀者能有效評估自己的進度和理解程度。
3. 對渡邊澄夫的開創性貝葉斯理論的全面指南,揭開曾被認為對資深統計學家來說過於艱深的主題的神秘面紗。
4. 詳細的源代碼和 Stan 代碼,將增強讀者對所呈現數學概念的理解。
5. 第六章對代數幾何主題的精簡處理,使貝葉斯理論更易於接觸且不再令人生畏。
開始您的機器學習和數據科學之旅,使用這本必備的教科書,今天就解鎖 WAIC 和 WBIC 的全部潛力!
作者簡介
Joe Suzuki is a professor of statistics at Osaka University, Japan.
作者簡介(中文翻譯)
鈴木喬(Joe Suzuki)是日本大阪大學的統計學教授。