線性代數(Williams 8/e) (8版)
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原文書資訊
書名:Linear Algebra with Applications 9/E 2018 <J&B>
作者: Williams
ISBN: 9781284120097
出版社: Jones & Bartlet
出版年: 2018年
書籍目路:
Part 1 Linear Equations, Vectors, and Matrices
Chapter 1 Linear Equations and Vectors
Chapter 2 Matrices and Linear Transformations
Chapter 3 Determinants and Eigenvectors
Part 2 Vector Spaces
Chapter 4 General Vector Spaces
Chapter 5 Coordinate Representations
Chapter 6 Inner Product Spaces
Part 3 Numerical Linear Algebra
Chapter 7 Numerical Methods
Chapter 8 Linear Programming
Appendix A Cross Product
Appendix B Equations of Planes and Lines in Three-Space
Appendix C Graphing Calculator Manual
Appendix D MATLAB Manual
中文書資訊
書名: 線性代數 Linear Algebra with Applications 8/E
作者: Williams/ 劉霈
ISBN: 9789865647032
出版社: 鼎隆
出版年: 2015年
書籍目錄:
Chapter 1 線性方程式及向量
Chapter 2 矩陣與線性轉換
Chapter 3 行列式及特徵值
Chapter 4 廣義向量空間
Chapter 5 座標表示
Chapter 6 內積空間
附錄A 外積
附錄B 三維空間中平面與直線之方程式
習題解答
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INTRODUCTION TO MATHEMATICAL STATISTICS (8版)
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Introduction to Mathematical Statistics, Global Edition
ISBN13:9781292264769
出版社:Pearson Education Limited
作者:Robert V. Hogg;Joeseph McKean;Allen T. Craig
裝訂/頁數:平裝/760頁
規格:20.7cm*25.5cm*2.1cm (高/寬/厚)
版次:8
出版日:2019/11/05
內容簡介
Comprehensive coverage of mathematical statistics – with a proven approach
Introduction to Mathematical Statistics by Hogg, McKean, and Craig enhances student comprehension and retention with numerous, illustrative examples and exercises. Classical statistical inference procedures in estimation and testing are explored extensively, and the text’s flexible organization makes it ideal for a range of mathematical statistics courses.
Substantial changes to the 8th Edition – many based on user feedback – help students appreciate the connection between statistical theory and statistical practice, while other changes enhance the development and discussion of the statistical theory presented.
1. Many additional real data sets to illustrate statistical methods or compare methods.
2. Expanded use of the statistical software R, a powerful statistical language which is free and can run on all three main platforms. However, instructors can choose another statistical package if desired.
3. Downloadable, supplemented mathematical review material in Appendix A: reviews sequences, infinite series, differentiation, and integration (univariate and bivariate).
4. Expanded discussion of iterated integrals, with added figures to clarify discussion.
5. A new subsection on the bivariate normal distribution begins the section on the multivariate normal distribution in Chapter 3 (Some Special Distributions).
6. Several important topics have been added, including Tukey’s multiple comparison procedure in Chapter 9 (Inferences About Normal Models)and confidence intervals for the correlation coefficients found in Chapters 9 and 10 (Nonparametric and Robust Statistics).
7. Discussion on standard errors for estimates obtained by bootstrapping the sample is now offered in Chapter 7 (Sufficiency).
Several topics that were discussed in the Exercises are now discussed in the text, including quantiles in Section 1.7.1 and hazard functions in Section 3.3.
目錄
Ch 1 Probability and Distributions
Ch 2 Multivariate Distributions
Ch 3 Some Special Distributions
Ch 4 Some Elementary Statistical Inferences
Ch 5 Consistency and Limiting Distributions
Ch 6 Maximum Likelihood Methods
Ch 7 Sufficiency
Ch 8 Optimal Tests of Hypotheses
Ch 9 Inferences About Normal Models
Ch10 Nonparametric and Robust Statistics
Ch11 Bayesian Statistics
原價:
1460
售價:
1314
現省:
146元
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Artificial Intelligence: Foundations of Computational Agents (3版)
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【簡介】
Introduces concepts at the right level of detail, using straightforward language and minimum mathematics
Examines the social and ethical impacts of AI, connecting techniques to real-world benefits and harms
Explains state-of-the-art algorithms and examples underlying the theory, demonstrating how concepts are applied
Provides two complementary software systems – AIPython and AILog - for experimentation and extension
Pedagogical features include examples, end-of-chapter reviews, further reading lists, and exercises
【目錄】
Part I - Agents in the World
Chapter 1 - Artificial Intelligence and Agents
Chapter 2 - Agent Architectures and Hierarchical Control
Part II - Reasoning and Planning with Certainty
Chapter 3 - Searching for Solutions
Chapter 4 - Reasoning with Constraints
Chapter 5 - Propositions and Inference
Chapter 6 - Deterministic Planning
Part III - Learning and Reasoning with Uncertainty
Chapter 7 - Supervised Machine Learning
Chapter 8 - Neural Networks and Deep Learning
Chapter 9 - Reasoning with Uncertainty
Chapter 10 - Learning with Uncertainty
Chapter 11 - Causality
Part IV - Planning and Acting with Uncertainty
Chapter 12 - Planning with Uncertainty
Chapter 13 - Reinforcement Learning
Chapter 14 - Multiagent Systems
Part V - Representing Individuals and Relations
Chapter 15 - Individuals and Relations
Chapter 16 - Knowledge Graphs and Ontologies
Chapter 17 - Relational Learning and Probabilistic Reasoning
Part VI - The Big Picture
Chapter 18 - The Social Impact of Artificial Intelligence
Chapter 19 - Retrospect and Prospect
Appendix A - Mathematical Preliminaries and Notation
Appendix B - Mapping to Open-Source Packages
原價:
1480
售價:
1376
現省:
104元
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Mathematical Foundations of Infinite-Dimensional Statistical Models (1版)
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Foundations of Computer Vision (Adaptive Computation and Machine Learning series) (1版)
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【簡介】
An accessible, authoritative, and up-to-date computer vision textbook offering a comprehensive introduction to the foundations of the field that incorporates the latest deep learning advances.
Machine learning has revolutionized computer vision, but the methods of today have deep roots in the history of the field. Providing a much-needed modern treatment, this accessible and up-to-date textbook comprehensively introduces the foundations of computer vision while incorporating the latest deep learning advances. Taking a holistic approach that goes beyond machine learning, it addresses fundamental issues in the task of vision and the relationship of machine vision to human perception. Foundations of Computer Vision covers topics not standard in other texts, including transformers, diffusion models, statistical image models, issues of fairness and ethics, and the research process. To emphasize intuitive learning, concepts are presented in short, lucid chapters alongside extensive illustrations, questions, and examples. Written by leaders in the field and honed by a decade of classroom experience, this engaging and highly teachable book offers an essential next-generation view of computer vision.
Up-to-date treatment integrates classic computer vision and deep learning
Accessible approach emphasizes fundamentals and assumes little background knowledge
Student-friendly presentation features extensive examples and images
Proven in the classroom
Instructor resources include slides, solutions, and source code
【目錄】
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FOUNDATIONS OF SUSTAINABLE BUSINESS, 3RD EDITION (3版)
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《中英合售》現代材料科學與工程 Foundations of Materials Science and Engineering/Smith
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2540
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現省:
152元
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