Fundamentals of Machine Elements 3/E SI Version (Adapted Edition) (1版)

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Fundamentals of Machine Elements 3/E SI Version (Adapted Edition) 作(編/譯)者 : Schmid & Hamrock & Jacobson／林靖國 改編 出版年份 : 2023 ISBN : 9789863783732 書號 : MX0537 幾色 : 2 規格 : 平裝 發行公司 : Taylor & Francis 英文書名中譯 : 機械設計 版次 : 3E 頁數 : 512 分別 : 原文書 Table of Contents: Part I  Fundamentals 1.  Introduction 2.  Load, Stress, and Strain 3.  Introduction to Materials and Manufacturing 4.  Stresses and Strains 5.  Deformation 6.  Failure Prediction for Static Loading 7.  Fatigue and Impact 8.  Lubrication, Friction, and Wear Part II  Machine Elements 9.  Shafting and Associated Parts 10.  Hydrodynamic and Hydrostatic Bearings 11.  Rolling-Element Bearings 12.  Helical, Bevel, and Worm Gears 13.  Fasteners, Connections, and Power Screws 14.  Springs 15.  Brakes and Clutches Appendix A: Physical and Mechanical Properties of Materials Appendix B: Stress-Strain Relationships Appendix C: Stress Intensity Factors for Some Common Crack Geometries Appendix D: Shear, Moment, and Deflection of Selected Beams Appendix E: Dimensions of Threaded Fasteners Index  　

Fundamentals of Machine Learning for Predictive Data Analytics (2版)

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Fundamentals of Machine Learning for Predictive Data Analytics, Second Edition: Algorithms, Worked Examples, and Case Studies 作者： Kelleher, John D.,Mac Namee, Brian,D’Arcy, Aoife 原文出版社：MIT Press 出版日期：2020/10/20 語言：英文 簡介 The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice.Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. This second edition covers recent developments in machine learning, especially in a new chapter on deep learning, and two new chapters that go beyond predictive analytics to cover unsupervised learning and reinforcement learning. The book is accessible, offering nontechnical explanations of the ideas underpinning each approach before introducing mathematical models and algorithms. It is focused and deep, providing students with detailed knowledge on core concepts, giving them a solid basis for exploring the field on their own. Both early chapters and later case studies illustrate how the process of learning predictive models fits into the broader business context. The two case studies describe specific data analytics projects through each phase of development, from formulating the business problem to implementation of the analytics solution. The book can be used as a textbook at the introductory level or as a reference for professionals.

Fundamentals of Machine Component Design (7版)

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Fundamentals of Machine Component Design 7/e 作者：Robert C. Juvinall, Kurt M. Marshek 原價：NT$ 1,800 ISBN：9781119590637 版次：7 年份：2020 出版商：John Wiley 頁數/規格：800頁/平裝單色 參考網頁：Fundamentals of Machine Component Design 7/e 內容簡介 Description Fundamentals of Machine Component Design presents a thorough introduction to the concepts and methods essential to mechanical engineering design, analysis, and application. In-depth coverage of major topics, including free body diagrams, force flow concepts, failure theories, and fatigue design, are coupled with specific applications to bearings, springs, brakes, clutches, fasteners, and more for a real-world functional body of knowledge. Critical thinking and problem-solving skills are strengthened through a graphical procedural framework, enabling the effective identification of problems and clear presentation of solutions. Solidly focused on practical applications of fundamental theory, this text helps students develop the ability to conceptualize designs, interpret test results, and facilitate improvement. Clear presentation reinforces central ideas with multiple case studies, in-class exercises, homework problems, computer software data sets, and access to supplemental internet resources, while appendices provide extensive reference material on processing methods, joinability, failure modes, and material properties to aid student comprehension and encourage self-study. 目錄 Table of Contents Part 1 Fundamentals Chapter 1 Mechanical Engineering design in Broad Perspective Chapter 2 Load Analysis Chapter 3 Materials Chapter 4 Static Body Stresses Chapter 5 Elastic Strain, Deflection, and Stability Chapter 6 Failure Theories, Safety Factors, and Reliability Chapter 7 Impact Chapter 8 Fatigue Chapter 9 Surface Damage Part 2 Applications Chapter 10 Threaded Fasteners and Power Screws Chapter 11 Rivets, Welding, and Bonding Chapter 12 Springs Chapter 13 Lubrication and Sliding Bearings Chapter 14 Rolling-Element Bearings Chapter 15 Spur Gears Chapter 16 Helical, Bevel, and Worm Gears Chapter 17 Shafts and Associated Parts Chapter 18 Clutches and Brakes Chapter 19 Belts, Chains, and Other Components Chapter 20 Micro/Nanoscale Machine Elements Chapter 21 Machine Component Interrelationships-A Case Study Chapter 22 Design and Fabrication of the Mechanical Systems for a Remote Control Car-A Design Project Case Study