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Grundzüge der Globalen Optimierung
by Oliver SteinDas vorliegende Lehrbuch ist eine Einführung in die globale Optimierung, die mathematische Sachverhalte einerseits stringent behandelt, sie aber andererseits auch sehr ausführlich motiviert und mit 75 Abbildungen illustriert. Das Buch richtet sich daher nicht nur an Mathematiker, sondern auch an Natur-, Ingenieur- und Wirtschaftswissenschaftler, die mathematisch fundierte Verfahren in ihrem Gebiet verstehen und anwenden möchten. Mit fast zweihundert Seiten stellt das Buch genügend Auswahlmöglichkeiten zur Verfügung, um es als Grundlage für unterschiedlich angelegte Vorlesungen zur globalen Optimierung zu verwenden. Die ausführliche Behandlung der globalen Lösbarkeit von Optimierungsproblemen unter anwendungsrelevanten Voraussetzungen setzt dabei einen neuen Akzent, der den Bestand der bisherigen Lehrbücher zur Optimierung bereichert. Anhand von Theorie und Algorithmen der glatten konvexen Optimierung verdeutlicht das Buch, dass die globale Lösung einer in der Praxis häufig auftretenden Klasse von Optimierungsproblemen effizient möglich ist, während es für die schwerer handhabbaren nichtkonvexen Probleme ausführlich die Ideen von Branch-and-Bound-Verfahren entwickelt.
Grundzüge der Globalen Optimierung
by Oliver SteinDas vorliegende Lehrbuch ist eine Einführung in die globale Optimierung, die mathematische Sachverhalte einerseits stringent behandelt, sie aber andererseits auch sehr ausführlich motiviert und mit 85 Abbildungen illustriert. Das Buch richtet sich daher nicht nur an Mathematiker, sondern auch an Natur-, Ingenieur- und Wirtschaftswissenschaftler, die mathematisch fundierte Verfahren in ihrem Gebiet verstehen und anwenden möchten. Mit fast zweihundert Seiten stellt das Buch genügend Auswahlmöglichkeiten zur Verfügung, um es als Grundlage für unterschiedlich angelegte Vorlesungen zur globalen Optimierung zu verwenden. Die ausführliche Behandlung der globalen Lösbarkeit von Optimierungsproblemen unter anwendungsrelevanten Voraussetzungen setzt dabei einen neuen Akzent, der den Bestand der bisherigen Lehrbücher zur Optimierung bereichert. Anhand von Theorie und Algorithmen der glatten konvexen Optimierung verdeutlicht das Buch, dass die globale Lösung einer in der Praxis häufig auftretenden Klasse von Optimierungsproblemen effizient möglich ist, während es für die schwerer handhabbaren nichtkonvexen Probleme ausführlich die Ideen von Branch-and-Bound-Verfahren entwickelt.Die vorliegende zweite Auflage wurde überarbeitet und um einige Passagen ergänzt.
Grundzüge der Kategorientheorie
by Christian MaurerDas Buch soll Mathematik-Studierenden eine Einführung in die Kategorientheorie geben. Nach einem einführenden Kapitel, in dem alle Grundbegriffe der Kategorientheorie definiert und erklärt werden, wird das Konzept der adjungierten Funktoren vorgestellt und gezeigt, was sie mit Lösungen universeller Probleme zu tun haben. Es folgt ein Kapitel über Limites, die sich als spezielle Adjunktionen entpuppen. In den letzten drei Kapiteln werden spezielle Kategorien vorstellt: Abelsche Kategorien, Monaden und elementare Topoi. Die Produktfamilie WissensExpress bietet Ihnen Lehr- und Lernbücher in kompakter Form. Die Bücher liefern schnell und verständlich fundiertes Wissen.
Grundzüge der Konvexen Analysis
by Oliver SteinDieses Lehrbuch gibt eine verständliche Einführung in die konvexe Analysis, die mathematische Sachverhalte einerseits stringent behandelt, sie aber andererseits auch sehr ausführlich motiviert und mit vielen Abbildungen illustriert. Die Resultate werden anhand der geometrisch leicht nachvollziehbaren Fragestellung entwickelt, wie sich Hindernismengen und Verbotszonen mit garantierten Sicherheitsabständen modellieren lassen. Der Stoffaufbau mittels dieses durchgängigen Beispiels setzt einen neuen Akzent, der den Bestand der bisherigen Lehrbücher zur konvexen Analysis bereichert. Die erzielten Ergebnisse werden zudem auf nichtglatte konvexe Optimierungsprobleme angewendet, die in den Ingenieur- und Wirtschaftswissenschaften eine wichtige Rolle spielen. Das Buch richtet sich daher nicht nur an Mathematiker, sondern auch an Natur-, Ingenieur- und Wirtschaftswissenschaftler, die mathematisch fundierte Verfahren in ihrem Gebiet verstehen und anwenden möchten. Für Dozenten stellt das Buch genügend Auswahlmöglichkeiten zur Verfügung, um es als Grundlage für unterschiedlich angelegte Vorlesungen zur konvexen Analysis zu verwenden.
Grundzüge der Nichtlinearen Optimierung
by Oliver SteinDas vorliegende Lehrbuch ist eine Einführung in die nichtlineare Optimierung, die mathematische Sachverhalte einerseits stringent behandelt, sie aber andererseits auch sehr ausführlich motiviert und mit 39 Abbildungen illustriert. Das Buch richtet sich daher nicht nur an Mathematiker, sondern auch an Natur-, Ingenieur- und Wirtschaftswissenschaftler, die mathematisch fundierte Verfahren in ihrem Gebiet verstehen und anwenden möchten. Mit fast zweihundert Seiten stellt das Buch genügend Auswahlmöglichkeiten zur Verfügung, um es als Grundlage für unterschiedlich angelegte Vorlesungen zur nichtlinearen Optimierung zu verwenden. Viele geometrische Ansätze für das Verständnis sowohl von Optimalitätsbedingungen als auch von numerischen Verfahren setzen dabei einen neuen Akzent, der den Bestand der bisherigen Lehrbücher zur Optimierung bereichert. Dies betrifft insbesondere die ausführliche Behandlung der Probleme, die durch verschiedene funktionale Beschreibungen derselben Geometrie der Menge zulässiger Punkte entstehen können, und die dadurch motivierte Einführung von Constraint Qualifications für die Herleitung ableitungsbasierter Optimalitätsbedingungen.
Grundzüge der Nichtlinearen Optimierung
by Oliver SteinDas vorliegende Lehrbuch ist eine Einführung in die nichtlineare Optimierung, die mathematische Sachverhalte einerseits stringent behandelt, sie aber andererseits auch sehr ausführlich motiviert und mit 42 Abbildungen illustriert. Das Buch richtet sich daher nicht nur an Mathematiker, sondern auch an Natur-, Ingenieur- und Wirtschaftswissenschaftler, die mathematisch fundierte Verfahren in ihrem Gebiet verstehen und anwenden möchten. Mit etwas mehr als zweihundert Seiten stellt das Buch genügend Auswahlmöglichkeiten zur Verfügung, um es als Grundlage für unterschiedlich angelegte Vorlesungen zur nichtlinearen Optimierung zu verwenden. Viele geometrische Ansätze für das Verständnis sowohl von Optimalitätsbedingungen als auch von numerischen Verfahren setzen dabei einen neuen Akzent, der den Bestand der bisherigen Lehrbücher zur Optimierung bereichert. Dies betrifft insbesondere die ausführliche Behandlung der Probleme, die durch verschiedene funktionale Beschreibungen derselben Geometrie der Menge zulässiger Punkte entstehen können, und die dadurch motivierte Einführung von Constraint Qualifications für die Herleitung ableitungsbasierter Optimalitätsbedingungen. Die vorliegende zweite Auflage wurde überarbeitet und um einige Passagen ergänzt.
Grundzüge der Parametrischen Optimierung
by Oliver SteinDieses Lehrbuch gibt eine verständliche Einführung in die parametrische Optimierung, die mathematische Sachverhalte einerseits stringent behandelt, sie aber andererseits auch sehr ausführlich motiviert und mit vielen Abbildungen illustriert. Die vorwiegend geometrische Herleitung von zentralen Stabilitätsresultaten setzt dabei einen neuen Akzent, der den Bestand der bisherigen Lehrbücher zur parametrischen Optimierung bereichert. Die Stabilitäts- und Sensitivitätsergebnisse werden nicht nur mit speziellen ökonomischen Fragestellungen illustriert, sondern auch auf größere Problemklassen wie Nash-Spiele und die semi-infinite Optimierung angewendet, die in den Ingenieur- und Wirtschaftswissenschaften wichtige eine Rolle spielen. Das Buch richtet sich daher nicht nur an Mathematiker, sondern auch an Natur-, Ingenieur- und Wirtschaftswissenschaftler, die mathematisch fundierte Verfahren in ihrem Gebiet verstehen und anwenden möchten. Für Dozenten stellt das Buch genügend Auswahlmöglichkeiten zur Verfügung, um es als Grundlage für unterschiedlich angelegte Vorlesungen zur parametrischen Optimierung zu verwenden.
Gröbner's Problem and the Geometry of GT-Varieties (RSME Springer Series #15)
by Liena Colarte-Gómez Rosa Maria Miró-RoigThis book presents progress on two open problems within the framework of algebraic geometry and commutative algebra: Gröbner's problem regarding the arithmetic Cohen-Macaulayness (aCM) of projections of Veronese varieties, and the problem of determining the structure of the algebra of invariants of finite groups. We endeavour to understand their unexpected connection with the weak Lefschetz properties (WLPs) of artinian ideals. In 1967, Gröbner showed that the Veronese variety is aCM and exhibited examples of aCM and nonaCM monomial projections. Motivated by this fact, he posed the problem of determining whether a monomial projection is aCM. In this book, we provide a comprehensive state of the art of Gröbner’s problem and we contribute to this question with families of monomial projections parameterized by invariants of a finite abelian group called G-varieties. We present a new point of view in the study of Gröbner’s problem, relating it to the WLP of Artinian ideals. GT varieties are a subclass of G varieties parameterized by invariants generating an Artinian ideal failing the WLP, called the Galois-Togliatti system. We studied the geometry of the G-varieties; we compute their Hilbert functions, a minimal set of generators of their homogeneous ideals, and the canonical module of their homogeneous coordinate rings to describe their minimal free resolutions. We also investigate the invariance of nonabelian finite groups to stress the link between projections of Veronese surfaces, the invariant theory of finite groups and the WLP. Finally, we introduce a family of smooth rational monomial projections related to G-varieties called RL-varieties. We study the geometry of this family of nonaCM monomial projections and we compute the dimension of the cohomology of the normal bundle of RL varieties. This book is intended to introduce Gröbner’s problem to young researchers and provide new points of view and directions for further investigations.
Guaranteed Computational Methods for Self-Adjoint Differential Eigenvalue Problems (SpringerBriefs in Mathematics)
by Xuefeng LiuThis monograph presents a study of newly developed guaranteed computational methodologies for eigenvalue problems of self-adjoint differential operators. It focuses on deriving explicit lower and upper bounds for eigenvalues, as well as explicit estimations for eigenfunction approximations. Such explicit error estimations rely on the finite element method (FEM) along with a new theory of explicit quantitative error estimation, diverging from traditional studies that primarily focus on qualitative results. To achieve quantitative error estimation, the monograph begins with an extensive analysis of the hypercircle method, that is, the Prager–Synge theorem. It introduces a novel a priori error estimation technique based on the hypercircle method. This facilitates the explicit estimation of Galerkin projection errors for equations such as Poisson's and Stokes', which are crucial for obtaining lower eigenvalue bounds via conforming FEMs. A thorough exploration of the fundamental theory of projection-based explicit lower eigenvalue bounds under a general setting of eigenvalue problems is also offered. This theory is extensively detailed when applied to model eigenvalue problems associated with the Laplace, biharmonic, Stokes, and Steklov differential operators, which are solved by either conforming or non-conforming FEMs. Moreover, there is a detailed discussion on the Lehmann–Goerisch theorem for the purpose of high-precision eigenvalue bounds, showing its relationship with previously established theorems, such as Lehmann–Maehly's method and Kato's bound. The implementation details of this theorem with FEMs, a topic rarely covered in existing literature, are also clarified. Lastly, the monograph introduces three new algorithms to estimate eigenfunction approximation errors, revealing the potency of classical theorems. Algorithm I extends Birkhoff’s result that works for simple eigenvalues to handle clustered eigenvalues, while Algorithm II generalizes the Davis–Kahan theorem, initially designed for strongly formulated eigenvalue problems, to address weakly formulated eigenvalue problems. Algorithm III utilizes the explicit Galerkin projection error estimation to efficiently handle Galerkin projection-based approximations.
Guesstimation 2.0: Solving Today's Problems on the Back of a Napkin
by Lawrence WeinsteinSimple and effective techniques for quickly estimating virtually anythingGuesstimation 2.0 reveals the simple and effective techniques needed to estimate virtually anything—quickly—and illustrates them using an eclectic array of problems. A stimulating follow-up to Guesstimation, this is the must-have book for anyone preparing for a job interview in technology or finance, where more and more leading businesses test applicants using estimation questions just like these.The ability to guesstimate on your feet is an essential skill to have in today's world, whether you're trying to distinguish between a billion-dollar subsidy and a trillion-dollar stimulus, a megawatt wind turbine and a gigawatt nuclear plant, or parts-per-million and parts-per-billion contaminants. Lawrence Weinstein begins with a concise tutorial on how to solve these kinds of order of magnitude problems, and then invites readers to have a go themselves. The book features dozens of problems along with helpful hints and easy-to-understand solutions. It also includes appendixes containing useful formulas and more.Guesstimation 2.0 shows how to estimate everything from how closely you can orbit a neutron star without being pulled apart by gravity, to the fuel used to transport your food from the farm to the store, to the total length of all toilet paper used in the United States. It also enables readers to answer, once and for all, the most asked environmental question of our day: paper or plastic?
Guesstimation: Solving the World's Problems on the Back of a Cocktail Napkin
by Lawrence Weinstein John AdamGuesstimation is a book that unlocks the power of approximation--it's popular mathematics rounded to the nearest power of ten! The ability to estimate is an important skill in daily life. More and more leading businesses today use estimation questions in interviews to test applicants' abilities to think on their feet. Guesstimation enables anyone with basic math and science skills to estimate virtually anything--quickly--using plausible assumptions and elementary arithmetic. Lawrence Weinstein and John Adam present an eclectic array of estimation problems that range from devilishly simple to quite sophisticated and from serious real-world concerns to downright silly ones. How long would it take a running faucet to fill the inverted dome of the Capitol? What is the total length of all the pickles consumed in the US in one year? What are the relative merits of internal-combustion and electric cars, of coal and nuclear energy? The problems are marvelously diverse, yet the skills to solve them are the same. The authors show how easy it is to derive useful ballpark estimates by breaking complex problems into simpler, more manageable ones--and how there can be many paths to the right answer. The book is written in a question-and-answer format with lots of hints along the way. It includes a handy appendix summarizing the few formulas and basic science concepts needed, and its small size and French-fold design make it conveniently portable. Illustrated with humorous pen-and-ink sketches, Guesstimation will delight popular-math enthusiasts and is ideal for the classroom.
Guide to 3D Vision Computation
by Kenichi Kanatani Yasuyuki Sugaya Yasushi KanazawaThis classroom-tested and easy-to-understand textbook/reference describes the state of the art in 3D reconstruction from multiple images, taking into consideration all aspects of programming and implementation. Unlike other computer vision textbooks, this guide takes a unique approach in which the initial focus is on practical application and the procedures necessary to actually build a computer vision system. The theoretical background is then briefly explained afterwards, highlighting how one can quickly and simply obtain the desired result without knowing the derivation of the mathematical detail. Features: reviews the fundamental algorithms underlying computer vision; describes the latest techniques for 3D reconstruction from multiple images; summarizes the mathematical theory behind statistical error analysis for general geometric estimation problems; presents derivations at the end of each chapter, with solutions supplied at the end of the book; provides additional material at an associated website.
Guide to Classical Physics: Using Mathematica for Calculations and Visualizations
by James W. RohlfThis is a “how to guide” for making introductory calculations in classical physics for undergraduates studying the subject.The calculations are performed in Mathematica, and stress graphical visualization, units, and numerical answers. The techniques show the student how to learn the physics without being hung up on the math. There is a continuing movement to introduce more advanced computational methods into lower-level physics courses. Mathematica is a unique tool in that code is written as "human readable" much like one writes a traditional equation on the board.The companion code for this book can be found here: https://physics.bu.edu/~rohlf/code.htmlKey Features:• Concise summary of the physics concepts• Over 300 worked examples in Mathematica• Tutorial to allow a beginner to produce fast resultsThe companion code for this book can be found here: https://physics.bu.edu/~rohlf/code.html
Guide to Cloud Computing for Business and Technology Managers: From Distributed Computing to Cloudware Applications
by Vivek KaleGuide to Cloud Computing for Business and Technology Managers: From Distributed Computing to Cloudware Applications unravels the mystery of cloud computing and explains how it can transform the operating contexts of business enterprises. It provides a clear understanding of what cloud computing really means, what it can do, and when it is practical
Guide to Discrete Mathematics
by Gerard O'ReganThis stimulating textbook presents a broad and accessible guide to the fundamentals of discrete mathematics, highlighting how the techniques may be applied to various exciting areas in computing. The text is designed to motivate and inspire the reader, encouraging further study in this important skill. Features: provides an introduction to the building blocks of discrete mathematics, including sets, relations and functions; describes the basics of number theory, the techniques of induction and recursion, and the applications of mathematical sequences, series, permutations, and combinations; presents the essentials of algebra; explains the fundamentals of automata theory, matrices, graph theory, cryptography, coding theory, language theory, and the concepts of computability and decidability; reviews the history of logic, discussing propositional and predicate logic, as well as advanced topics; examines the field of software engineering, describing formal methods; investigates probability and statistics.
Guide to Discrete Mathematics: An Accessible Introduction to the History, Theory, Logic and Applications (Texts in Computer Science)
by Gerard O'ReganThis stimulating textbook presents a broad and accessible guide to the fundamentals of discrete mathematics, highlighting how the techniques may be applied to various exciting areas in computing. The text is designed to motivate and inspire the reader, encouraging further study in this important skill. Features: This book provides an introduction to the building blocks of discrete mathematics, including sets, relations and functions; describes the basics of number theory, the techniques of induction and recursion, and the applications of mathematical sequences, series, permutations, and combinations; presents the essentials of algebra; explains the fundamentals of automata theory, matrices, graph theory, cryptography, coding theory, language theory, and the concepts of computability and decidability; reviews the history of logic, discussing propositional and predicate logic, as well as advanced topics such as the nature of theorem proving; examines the field of software engineering, including software reliability and dependability and describes formal methods; investigates probability and statistics and presents an overview of operations research and financial mathematics.
Guide to Modern Physics: Using Mathematica for Calculations and Visualizations
by James W. RohlfThis is a "how to guide" for making beginning calculations in modern physics. The academic level is second year college physical science and engineering students. The calculations are performed in Mathematica, and stress graphical visualization, units, and numerical answers. The techniques show the student how to learn the physics without being hung up on the math. There is a continuing movement to introduce more advanced computational methods into lower-level physics courses. Mathematica is a unique tool in that code is written as "human readable" much like one writes a traditional equation on the board. Key Features: Concise summary of the physics concepts. Over 300 worked examples in Mathematica. Tutorial to allow a beginner to produce fast results. The companion code for this book can be found here: https://physics.bu.edu/~rohlf/code.html James Rohlf is a Professor at Boston University. As a graduate student he worked on the first experiment to trigger on hadron jets with a calorimeter, Fermilab E260. His thesis (G. C. Fox, advisor, C. Barnes, R. P. Feynman, R. Gomez) used the model of Field and Feynman to compare observed jets from hadron collisions to that from electron-positron collisions and made detailed acceptance corrections to arrive at first the measurement of quark-quark scattering cross sections. His thesis is published in Nuclear Physics B171 (1980) 1. At the Cornell Electron Storage Rings, he worked on the discovery of the Upsilon (4S) resonance and using novel event shape variables developed by Stephen Wolfram and his thesis advisor, Geoffrey Fox. He performed particle identification of kaons and charmed mesons to establish the quark decay sequence, b –> c. At CERN, he worked on the discovery of the W and Z bosons and measurement of their properties. Presently, he is working on the Compact Muon Solenoid (CMS) experiment at the CERN Large Hadron Collider (LHC) which discovered the Higgs boson and is searching for new phenomena beyond the standard model.
Guide to Pairing-Based Cryptography (Chapman & Hall/CRC Cryptography and Network Security Series)
by Nadia El Mrabet; Marc JoyeThis book is devoted to efficient pairing computations and implementations, useful tools for cryptographers working on topics like identity-based cryptography and the simplification of existing protocols like signature schemes. As well as exploring the basic mathematical background of finite fields and elliptic curves, Guide to Pairing-Based Cryptography offers an overview of the most recent developments in optimizations for pairing implementation. Each chapter includes a presentation of the problem it discusses, the mathematical formulation, a discussion of implementation issues, solutions accompanied by code or pseudocode, several numerical results, and references to further reading and notes. Intended as a self-contained handbook, this book is an invaluable resource for computer scientists, applied mathematicians and security professionals interested in cryptography.
Guide to Programming for the Digital Humanities: Lessons For Introductory Python (SpringerBriefs in Computer Science)
by Brian KokenspargerAs an introduction to programming for the Digital Humanities (DH), this book presents six key assignments oriented on DH topics. The topics include Computing Change Over Time (calculating burials at a historic cemetery), Visualizing Change Over Time (visualizing the burials at the historic cemetery), Textual Analysis (finding word frequencies and “stop words” in public domain texts), XML Transformation (transforming a simplified version of XML into HTML styled with CSS), Stylometry (comparing the measured features of graphic images), and Social Network Analysis (analyzing extended relationships in historic circles). The book focuses on the practical application of these assignments in the classroom, providing a range of variations for each assignment, which can be selected on the basis of students’ specific programming background and skills; “atomic” assignments, which can be used to give students the experience they need to successfully complete the main assignments; and some common pitfalls and gotchas to manage in the classroom. The book’s chief goals are to introduce novice computer science (CS) students to programming for DH, and to offer them valuable hands-on experience with core programming concepts.
Guide to Software Verification with Frama-C: Core Components, Usages, and Applications (Computer Science Foundations and Applied Logic)
by Nikolai Kosmatov Virgile Prevosto Julien SignolesFrama-C is a popular open-source toolset for analysis and verification of C programs, largely used for teaching, experimental research, and industrial applications.With the growing complexity and ubiquity of modern software, there is increasing interest in code analysis tools at various levels of formalization to ensure safety and security of software products. Acknowledging the fact that no single technique will ever be able to fit all software verification needs, the Frama-C platform features a wide set of plug-ins that can be used or combined for solving specific verification tasks. This guidebook presents a large panorama of basic usages, research results, and concrete applications of Frama-C since the very first open-source release of the platform in 2008. It covers the ACSL specification language, core verification plug-ins, advanced analyses and their combinations, key ingredients for developing new plug-ins, as well as successful industrial case studies in which Frama-C has helped engineers verify crucial safety or security properties. Topics and features:* Gentle, example-based introduction to software specification and verification * Wide panorama of state-of-the-art specification and analysis techniques * Step-by-step guide to develop your own, tailor-made analysis on top of the platform* Inspiring success stories of Frama-C deployment on industrial code* More than 15 years of R&D on analysis and verification of C codeThis book is firmly rooted on the practice of software analysis, with numerous examples, exercises and application guidelines. As such, it is particularly well suited for software verification practitioners wishing to deploy verification on their code, as well as for undergraduate students with little or no experience in code analysis techniques. More advanced sections on the theoretical underpinnings of the analyzers will be of interest for graduate students and researchers.Nikolai Kosmatov is a Senior Researcher at Thales Research & Technology, France. Virgile Prevosto is a Senior Researcher and Julien Signoles is a Research Director, both at Université Paris-Saclay, CEA, List, France.
Guide to Teaching Data Science: An Interdisciplinary Approach
by Orit Hazzan Koby MikeData science is a new field that touches on almost every domain of our lives, and thus it is taught in a variety of environments. Accordingly, the book is suitable for teachers and lecturers in all educational frameworks: K-12, academia and industry.This book aims at closing a significant gap in the literature on the pedagogy of data science. While there are many articles and white papers dealing with the curriculum of data science (i.e., what to teach?), the pedagogical aspect of the field (i.e., how to teach?) is almost neglected. At the same time, the importance of the pedagogical aspects of data science increases as more and more programs are currently open to a variety of people.This book provides a variety of pedagogical discussions and specific teaching methods and frameworks, as well as includes exercises, and guidelines related to many data science concepts (e.g., data thinking and the data science workflow), main machine learning algorithms and concepts (e.g., KNN, SVM, Neural Networks, performance metrics, confusion matrix, and biases) and data science professional topics (e.g., ethics, skills and research approach).Professor Orit Hazzan is a faculty member at the Technion’s Department of Education in Science and Technology since October 2000. Her research focuses on computer science, software engineering and data science education. Within this framework, she studies the cognitive and social processes on the individual, the team and the organization levels, in all kinds of organizations.Dr. Koby Mike is a Ph.D. graduate from the Technion's Department of Education in Science and Technology under the supervision of Professor Orit Hazzan. He continued his post-doc research on data science education at the Bar-Ilan University, and obtained a B.Sc. and an M.Sc. in Electrical Engineering from Tel Aviv University.
Guidebook to R Graphics Using Microsoft® Windows
by Kunio TakezawaIntroduces the graphical capabilities of R to readers new to the software Due to its flexibility and availability, R has become the computing software of choice for statistical computing and generating graphics across various fields of research. Guidebook to R Graphics Using Microsoft® Windows offers a unique presentation of R, guiding new users through its many benefits, including the creation of high-quality graphics. Beginning with getting the program up and running, this book takes readers step by step through the process of creating histograms, boxplots, strip charts, time series graphs, steam-and-leaf displays, scatterplot matrices, and map graphs. In addition, the book presents: Tips for establishing, saving, and printing graphs along with essential base-package plotting functions Interactive R programs for carrying out common tasks such as inputting values, moving data on a natural spline, adjusting three-dimensional graphs, and understanding simple and local linear regression Various external packages for R that help to create more complex graphics like rimage, gplots, ggplot2, tripack, rworldmap, and plotrix packages Throughout the book, concise explanations of key concepts of R graphics assist readers in carrying out the presented procedures, and any coverage of functions is clearly written out and displayed in the text as demos. The discussed techniques are accompanied by a wealth of screenshots and graphics with related R code available on the book's FTP site, and numerous exercises allow readers to test their understanding of the presented material. Guidebook to R Graphics Using Microsoft® Windows is a valuable resource for researchers in the fields of statistics, public health, business, and the life and social sciences who use or would like to learn how to use R to create visual representations of data. The book can also be used as a supplement for courses on statistical analysis at the upper-undergraduate level.
Guided Math Lessons in Fifth Grade: Getting Started
by Nicki NewtonGuided Math Lessons in Fifth Grade provides detailed lessons to help you bring guided math groups to life. Based on the bestselling Guided Math in Action, this practical book offers 16 lessons, taught in a round of 3—concrete, pictorial and abstract. The lessons are based on the priority standards and cover fluency, word problems, fractions, and decimals. Author Dr. Nicki Newton shows you the content, as well as the practices and processes, that should be worked on in the lessons so that students not only learn the content but also how to solve problems, reason, communicate their thinking, model, use tools, use precise language and see structure and patterns. Throughout the book, you’ll find tools, templates and blackline masters so that you can instantly adapt the lesson to your specific needs and use it right away. With the easy-to-follow plans in this book, students can work more effectively in small guided math groups—and have loads of fun along the way! Remember that guided math groups are about doing the math. So throughout these lessons, you will see students working with manipulatives to make meaning, doing mathematical sketches to show what they understand and can make sense of the abstract numbers. When students are given the opportunities to make sense of the math in hands-on and visual ways, then the math begins to make sense to them!
Guided Math Lessons in First Grade: Getting Started
by Nicki NewtonGuided Math Lessons in First Grade provides detailed lessons to help you bring guided math groups to life. Based on the bestselling Guided Math in Action, this practical book offers 16 lessons, taught in a round of 3—concrete, pictorial, and abstract. The lessons are based on the priority standards and cover fluency, word problems, operations and algebraic thinking, and place value. Author Dr. Nicki Newton shows you the content as well as the practices and processes that should be worked on in the lessons, so that students not only learn the content but also how to solve problems, reason, communicate their thinking, model, use tools, use precise language, and see structure and patterns. Throughout the book, you’ll find tools, templates, and blackline masters so that you can instantly adapt the lesson to your specific needs and use it right away. With the easy-to-follow plans in this book, students can work more effectively in small guided math groups—and have loads of fun along the way!
Guided Math Lessons in Fourth Grade: Getting Started
by Nicki NewtonGuided Math Lessons in Fourth Grade provides detailed lessons to help you bring guided math groups to life. Based on the bestselling Guided Math in Action, this practical book offers 16 lessons, taught in a round of three–concrete, pictorial and abstract. The lessons are based on the priority standards and cover fluency, word problems, fractions and place value. Author Dr. Nicki Newton shows you the content as well as the practices and processes that should be worked on in the lessons, so that students not only learn the content but also how to solve problems, reason, communicate their thinking, model, use tools, use precise language, and see structure and patterns. Throughout the book, you’ll find tools, templates and blackline masters so that you can instantly adapt the lesson to your specific needs and use it right away. With the easy-to-follow plans in this book, students can more work effectively in small guided math groups—and have loads of fun along the way! Remember that guided math groups are about doing the math. So doing mathematical sketches to show what they understand and can make sense of the abstract numbers. When students are given the opportunities to make sense of the math in hands-on and visual ways, then the math begins to make sense!