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Nussbaumer Knaflic Cole: Storytelling
with Data Box Set

Storytelling with Data Box Set

Series on Concrete & Applicable Mathematics

Rainbow And Properly Colored Subgraphs

Essays in Developmental Psychology

Perspectives from Developmental Psychology

Attitudes and Emotions Towards Mathematics

Many of the deepest and most important areas of mathematics have arisen from questions about extremes - shortest lines, smallest areas, densest packings, fewest colours. Mathematicians have been grappling with such issues for centuries, and some go back thousands of years. The isoperimetric problem, for example - which asks for the shortest path enclosing a given area - dates back to the mythological founding of the city of Carthage. By contrast, it was only in 2017 that the densest ways to pack identical spheres into a space of 24 dimensions was finally proved. Many of these problems are more than mere thought experiments. The origins of the Travelling Salesperson Problem - find the shortest route that visits a given set of cities - are self-explanatory. The Plateau problem, about the geometry of soap bubbles, now has applications as diverse as cosmology and biological development. Reaching for the Extreme tells the stories of these and other similar problems: their historical roots, the struggles to solve them, and the uses that can be made of the results, when such uses exist.

How the Quest for the Biggest, Fewest and Weirdest Makes Maths

Reaching for the Extreme

An Introduction to the Finite Element Method with the Variational Approach offers a comprehensive solution to the gaps often found in introductory texts on the Finite Element Method (FEM). The book provides a thorough introduction to the fundamental principles of linear and time-independent FEM within the variational framework. It meticulously covers the derivation of 1-D FEM equations based on variational functionals, encompassing both linear and higher-order elements, and shape functions driven by convergence criteria. Furthermore, it explores 1-D numerical integration, outlines coding procedures, and provides insights into handling material nonlinearity and time-dependent scenarios. Expanding into 2-D problems, the book offers derivations of 2-D FEM equations tailored to diverse engineering disciplines, including Steady-State Heat Conduction, Solid Mechanics (covering torsion, plane strain/axisymmetric cases, and the bending, stability, and vibrations of thin plates), as well as Fluid Mechanics (addressing incompressible inviscid and viscous fluids). It includes detailed discussions on element continuity, numerical integration techniques, and even includes 2-D codes for selected problems. The book concludes by delving into recent advancements in FEM, with a specific focus on applications in machine learning and isogeometric analysis.

An Introduction to the Finite Element Method with the Variational Approach

Advances in Computers

Quantum Machine Learning (QML): Platform, Tools and Applications: Volume 140

Extended Hypergeometric Functions and Orthogonal Polynomials

Tauche ein in die Elektrodynamik mit einem Lehrbuch, welches die Maxwellschen Gleichungen als Ausgangspunkt nutzt, wodurch Schritt für Schritt ein tiefes Verständnis vermittelt wird.&nbsp;Besonderheiten:Dieses Buch beginnt jedes Kapitel mit einer der Maxwellschen Gleichungen und erklärt dann schrittweise die einzelnen Bestandteile.&nbsp;Anfänger/innen haben so ein konkretes Lernziel vor Augen.&nbsp;Sowohl die vorkommenden physikalischen Größen als auch mathematischen Grundlagen werden in ihrem natürlichen Kontext erklärt. Grundlegende Prinzipien und komplexe Konzepte werden für verschiedene Fälle betrachtet und mit einfachen Beispielen verdeutlicht. Mithilfe von Aufgaben und Lösungen – sowohl klassisch im Buch als auch als digitale Karteikarten für unterwegs – kann das erworbene Wissen eingeübt und vertieft werden.&nbsp;Inhalt:1. Das Gaußsche Gesetz für elektrische Felder – 2. Das Gaußsche Gesetz für magnetische Felder –&nbsp;3. Das Faradaysche Induktionsgesetz&nbsp;– 4. Das Ampère-Maxwellsche Gesetz – 5. Weiterführende Themen der Elektrodynamik – 6. Wechselwirkung von elektrischen und magnetischen Feldern mit Materie&nbsp;Zielgruppe:Studierende der Ingenieurwissenschaften und Naturwissenschaften, wie z.B. Elektrotechnik, Physik, Medizinphysik, etc. als auch Interessierte bzw. Berufstätige, die ein tieferes Verständnis für die Grundlagen der Elektrodynamik entwickeln möchten.&nbsp;Vorkenntnisse: Hilfreich sind physikalische Grundkenntnisse wie sie z.B. im Buch Vorkurs Physik fürs MINT-Studium vermittelt werden.&nbsp;Der Autor:Dr. Patrick Steglich&nbsp;promovierte 2017 an der Universität Rom ‚Tor Vergata‘ und habilitierte 2023 an der Brandenburgischen Technischen Universität Cottbus-Senftenberg.&nbsp;Seit 2018 ist er Dozent mit Lehrauftrag an der Technischen Hochschule Wildau&nbsp;für das Fach Elektrodynamik und forscht am Leibniz-Institut für innovative Mikroelektronik.

Eine schrittweise Reise durch Maxwells Gleichungen

Klassische Elektrodynamik

A hands-on approach to preparing your company for AI-powered digital transformation In Monster Transformation: Conquer Your Digital Fears, Be AI Ready, and Focus on What Matters to Your Organization, a team of veteran digital leaders delivers an expert framework to digital transformation that focuses on the competencies your employees will need to have-and develop-to enable your organization to function in a world defined by generative artificial intelligence. Monster Transformation blends actionable insights, real-world case studies, and immediately recognizable organizational behaviors that can either move forward or derail transformation in the age of AI. Whether you are leading, a part of, supporting or interested in organizational transformation, this book challenges conventional thought on dealing with transformation, provides insights on how and why barriers to effective change arise and pragmatic mechanisms to address challenges, diminish barriers and leverage employees. You'll also find: <ul> <li>Examples of transformation blockers and obstacles, as well as the steps you need to take to eliminate and overcome them</li> <li>Real-world insights from interviews with transformation leaders across industries and organizational layers </li> <li>10 incisive case studies from well-known brands including Ferrari, Instacart, Patagonia, Brooks Running, and Calm, hands-on scenarios, chapter exercises, and actionable takeaways you can apply immediately at your own organization</li> </ul> Perfect for managers, executives, and other business leaders, Monster Transformation offers a practical approach for implementing the world's newest, most exciting technologies in your company. With a foreword by Shellye Archambeau, bestselling author of Unapologetically Ambitious, Monster Transformation is a no-BS humanistic take on how organizations can adapt and thrive in a chaotic and turbulent environment.

Conquer Your Digital Fears, Be AI Ready, and Focus on What Matters to Your Organization

Monster Transformation

Why Not Nonlinear Algebra: Math, Science, Applications And Funding

Microsoft Power BI For Dummies

While the field of Deep Learning has been advancing at frightening speeds during the last ten years, we do not have a plausible theoretical explanation of its success yet. One can safely say that Deep Learning works, but nobody really understands why. Nevertheless, starting around five years before now, a decent number of theoretical papers specifically concerning neural nets started to emerge at top machine learning venues. This makes us think that the core of Deep Learning theory has already started to crystallize.The goal of the present book is to present these core concepts of Deep Learning theory to readers so that they could directly dive into recent papers of this area. For this purpose, each chapter elaborates a simple model or a classical result in details first and then discusses possible generalizations and more recent developments of the same idea.We have to warn the reader that the present book is not a mathematical manuscript. Not all results here are stated as formal theorems and not all theorems are provided with complete and rigorous proofs. Many of the theorems of the book are proven up to some technical lemmas, while for some there is only a proof sketch. This conforms with the main idea of the book: present and illustrate concepts rather than reproduce all the results.The book, in its present form, covers the following topics: uniform generalization bounds, PAC-bayesian generalization bounds, double descent phenomena, infinitely-wide networks, implicit bias of gradient descent, loss landscape, gradient descent convergence guarantees, and initialization strategies.

Elements Of Deep Learning Theory

This book presents a comprehensive treatment of pricing and hedging soccer betting contracts using the modern techniques of probability, statistics, finance, and portfolio management. It introduces betting in general and then addresses the probabilistic intuition needed in the more complex world of soccer betting. The author presents an innovative perspective by thinking about betting odds in terms of the expected number of goals of both teams. In addition, when the betting market is in play, the book treats betting before the game and during the game separately.

Science of Soccer Statistics

Soccermetrics

Storytelling with Data Box Set

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