Produkt zum Begriff Algorithms-for-Approximation:
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Graph Algorithms for Data Science
Graphs are the natural way to understand connected data. This book explores the most important algorithms and techniques for graphs in data science, with practical examples and concrete advice on implementation and deployment.In Graph Algorithms for Data Science you will learn:Labeled-property graph modelingConstructing a graph from structured data such as CSV or SQLNLP techniques to construct a graph from unstructured dataCypher query language syntax to manipulate data and extract insightsSocial network analysis algorithms like PageRank and community detectionHow to translate graph structure to a ML model input with node embedding modelsUsing graph features in node classification and link prediction workflowsGraph Algorithms for Data Science is a hands-on guide to working with graph-based data in applications like machine learning, fraud detection, and business data analysis. It's filled with fascinating and fun projects, demonstrating the ins-and-outs of graphs. You'll gain practical skills by analyzing Twitter, building graphs with NLP techniques, and much more. You don't need any graph experience to start benefiting from this insightful guide. These powerful graph algorithms are explained in clear, jargon-free text and illustrations that makes them easy to apply to your own projects.about the technologyGraphs reveal the relationships in your data. Tracking these interlinking connections reveals new insights and influences and lets you analyze each data point as part of a larger whole. This interconnected data is perfect for machine learning, as well as analyzing social networks, communities, and even product recommendations.about the bookGraph Algorithms for Data Science teaches you how to construct graphs from both structured and unstructured data. You'll learn how the flexible Cypher query language can be used to easily manipulate graph structures, and extract amazing insights. The book explores common and useful graph algorithms like PageRank and community detection/clustering algorithms. Each new algorithm you learn is instantly put into action to complete a hands-on data project, including modeling a social network! Finally, you'll learn how to utilize graphs to upgrade your machine learning, including utilizing node embedding models and graph neural networks.
Preis: 56.7 € | Versand*: 0 € -
Algorithms
The leading introduction to computer algorithms in use today, including fifty algorithms every programmer should knowPrinceton Computer Science professors, Robert Sedgewick and Kevin Wayne, survey the most important computer algorithms in use and of interest to anyone working in science, mathematics, and engineering, and those who use computation in the liberal arts. They provide a full treatment of data structures and algorithms for key areas that enable you to confidently implement, debug, and put them to work in any computational environment. Fundamentals: Basic programming modelsData abstractionBags, queues, and stacksAnalysis of algorithms SortingElementary sortsMergesortQuicksortPriority queuesApplications GraphsUndirected graphsDirected graphsMinimum spanning treesShortest pathsStringsString sortsTriesSubstring searchRegular expressionsData compressionThese algorithms are generally ingenious creations that, remarkably, can each be expressed in just a dozen or two lines of code. As a group, they represent problem-solving power of amazing scope. They have enabled the construction of computational artifacts, the solution of scientific problems, and the development of commercial applications that would not have been feasible without them.
Preis: 81.31 € | Versand*: 0 € -
Algorithms in Java, Part 5: Graph Algorithms: Graph Algorithms
Once again, Robert Sedgewick provides a current and comprehensive introduction to important algorithms. The focus this time is on graph algorithms, which are increasingly critical for a wide range of applications, such as network connectivity, circuit design, scheduling, transaction processing, and resource allocation. In this book, Sedgewick offers the same successful blend of theory and practice that has made his work popular with programmers for many years. Michael Schidlowsky and Sedgewick have developed concise new Java implementations that both express the methods in a natural and direct manner and also can be used in real applications. Algorithms in Java, Third Edition, Part 5: Graph Algorithms is the second book in Sedgewick's thoroughly revised and rewritten series. The first book, Parts 1-4, addresses fundamental algorithms, data structures, sorting, and searching. A forthcoming third book will focus on strings, geometry, and a range of advanced algorithms. Each book's expanded coverage features new algorithms and implementations, enhanced descriptions and diagrams, and a wealth of new exercises for polishing skills. The natural match between Java classes and abstract data type (ADT) implementations makes the code more broadly useful and relevant for the modern object-oriented programming environment. The Web site for this book (www.cs.princeton.edu/~rs/) provides additional source code for programmers along with a variety of academic support materials for educators. Coverage includes: A complete overview of graph properties and typesDiagraphs and DAGs Minimum spanning treesShortest paths Network flowsDiagrams, sample Java code, and detailed algorithm descriptions A landmark revision, Algorithms in Java, Third Edition, Part 5 provides a complete tool set for programmers to implement, debug, and use graph algorithms across a wide range of computer applications.
Preis: 43.86 € | Versand*: 0 € -
Algorithms in C++ Part 5: Graph Algorithms
Once again, Robert Sedgewick provides a current and comprehensive introduction to important algorithms. The focus this time is on graph algorithms, which are increasingly critical for a wide range of applications, such as network connectivity, circuit design, scheduling, transaction processing, and resource allocation. In this book, Sedgewick offers the same successful blend of theory and practice that has made his work popular with programmers for many years. Christopher van Wyk and Sedgewick have developed concise new C++ implementations that both express the methods in a natural and direct manner and also can be used in real applications. Algorithms in C++, Third Edition, Part 5: Graph Algorithms is the second book in Sedgewick's thoroughly revised and rewritten series. The first book, Parts 1-4, addresses fundamental algorithms, data structures, sorting, and searching. A forthcoming third book will focus on strings, geometry, and a range of advanced algorithms. Each book's expanded coverage features new algorithms and implementations, enhanced descriptions and diagrams, and a wealth of new exercises for polishing skills. A focus on abstract data types makes the programs more broadly useful and relevant for the modern object-oriented programming environment. Coverage includes: A complete overview of graph properties and types Diagraphs and DAGs Minimum spanning trees Shortest paths Network flows Diagrams, sample C++ code, and detailed algorithm descriptions The Web site for this book (http://www.cs.princeton.edu/~rs/) provides additional source code for programmers along with a wide range of academic support materials for educators. A landmark revision, Algorithms in C++, Third Edition, Part 5 provides a complete tool set for programmers to implement, debug, and use graph algorithms across a wide range of computer applications.
Preis: 27.81 € | Versand*: 0 €
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Wie kann man mithilfe von Approximation mathematische Funktionen oder Werte annähern? Welche Methoden werden in der Approximation verwendet?
Man kann mathematische Funktionen oder Werte mithilfe von Approximation durch die Verwendung von Näherungswerten oder vereinfachten Modellen annähern. Zu den Methoden der Approximation gehören beispielsweise die Taylor-Reihe, die Interpolation oder die Methode der kleinsten Quadrate. Diese Methoden helfen dabei, komplexe Funktionen oder Werte durch einfachere Ausdrücke oder Modelle zu ersetzen, um eine annähernde Lösung zu erhalten.
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Wie kann man Approximation in der Mathematik verwenden, um komplexe Probleme zu lösen? Welche Methoden der Approximation werden in der Naturwissenschaft angewendet?
Approximation in der Mathematik ermöglicht es, komplexe Probleme durch Annäherungslösungen zu lösen, wenn exakte Lösungen nicht möglich sind. In der Naturwissenschaft werden Methoden wie lineare Approximation, Taylor-Entwicklung und numerische Verfahren wie Finite-Elemente-Analyse verwendet, um komplexe Phänomene zu modellieren und zu verstehen. Diese Approximationsmethoden helfen Wissenschaftlern, realistische Modelle zu erstellen und Vorhersagen über das Verhalten von Systemen zu treffen.
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Wann wird for benutzt?
For wird verwendet, um den Zweck oder das Ziel einer Handlung oder einer Aktivität auszudrücken. Zum Beispiel: "Ich gehe zum Supermarkt, um Lebensmittel zu kaufen." For wird auch verwendet, um die Dauer einer Handlung oder einer Aktivität anzugeben. Zum Beispiel: "Ich habe für zwei Stunden an meinem Projekt gearbeitet." For kann auch verwendet werden, um eine Zeitperiode anzugeben. Zum Beispiel: "Ich werde für eine Woche im Urlaub sein." For wird auch verwendet, um den Empfänger oder Nutznießer einer Handlung oder einer Aktivität zu benennen. Zum Beispiel: "Ich habe ein Geschenk für meine Mutter gekauft."
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Welche Werte für x und Approximation gibt es in Geogebra?
In Geogebra können verschiedene Werte für x und Approximation verwendet werden, je nach den Bedürfnissen des Benutzers. Die Werte für x können beliebige reale Zahlen sein, die in den gegebenen Bereich fallen. Die Approximation kann je nach Funktion und Genauigkeitsanforderungen des Benutzers variieren, von einer einfachen linearen Approximation bis hin zu komplexeren Methoden wie der Polynomapproximation oder der Taylor-Reihenapproximation.
Ähnliche Suchbegriffe für Algorithms-for-Approximation:
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Algorithms in C, Part 5: Graph Algorithms
Once again, Robert Sedgewick provides a current and comprehensive introduction to important algorithms. The focus this time is on graph algorithms, which are increasingly critical for a wide range of applications, such as network connectivity, circuit design, scheduling, transaction processing, and resource allocation. In this book, Sedgewick offers the same successful blend of theory and practice with concise implementations that can be tested on real applications, which has made his work popular with programmers for many years. Algorithms in C, Third Edition, Part 5: Graph Algorithms is the second book in Sedgewick's thoroughly revised and rewritten series. The first book, Parts 1-4, addresses fundamental algorithms, data structures, sorting, and searching. A forthcoming third book will focus on strings, geometry, and a range of advanced algorithms. Each book's expanded coverage features new algorithms and implementations, enhanced descriptions and diagrams, and a wealth of new exercises for polishing skills. A focus on abstract data types makes the programs more broadly useful and relevant for the modern object-oriented programming environment. Coverage includes: A complete overview of graph properties and types Diagraphs and DAGs Minimum spanning trees Shortest paths Network flows Diagrams, sample C code, and detailed algorithm descriptions The Web site for this book (http://www.cs.princeton.edu/~rs/) provides additional source code for programmers along with numerous support materials for educators. A landmark revision, Algorithms in C, Third Edition, Part 5 provides a complete tool set for programmers to implement, debug, and use graph algorithms across a wide range of computer applications.
Preis: 51.35 € | Versand*: 0 € -
Grokking Algorithms
A friendly, fully-illustrated introduction to the most important computer programming algorithms. The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. This book will prepare you for those pesky algorithms questions in every programming job interview and help you apply them in your day-to-day work. And if you want to understand them without slogging through dense multipage proofs, this is the book for you. In Grokking Algorithms, Second Edition you will discover: Search, sort, and graph algorithms Data structures such as arrays, lists, hash tables, trees, and graphs NP complete and greedy algorithms Performance trade-offs between algorithms Exercises and code samples in every chapter Over 400 illustrations with detailed walkthroughs The first edition of Grokking Algorithms proved to over 100,000 readers that learning algorithms doesn't have to be complicated or boring! This new edition now includes fresh coverage of trees, NP complete problems, and code updates to Python 3. With easy-to-read, friendly explanations, clever examples, and exercises to sharpen your skills as you learn, youll actually enjoy learning these important algorithms.
Preis: 60.98 € | Versand*: 0 € -
Algorithms, Part II
This book is Part II of the fourth edition of Robert Sedgewick and Kevin Wayne’s Algorithms, the leading textbook on algorithms today, widely used in colleges and universities worldwide. Part II contains Chapters 4 through 6 of the book. The fourth edition of Algorithms surveys the most important computer algorithms currently in use and provides a full treatment of data structures and algorithms for sorting, searching, graph processing, and string processing -- including fifty algorithms every programmer should know. In this edition, new Java implementations are written in an accessible modular programming style, where all of the code is exposed to the reader and ready to use. The algorithms in this book represent a body of knowledge developed over the last 50 years that has become indispensable, not just for professional programmers and computer science students but for any student with interests in science, mathematics, and engineering, not to mention students who use computation in the liberal arts. The companion web site, algs4.cs.princeton.edu contains An online synopsis Full Java implementations Test data Exercises and answers Dynamic visualizations Lecture slides Programming assignments with checklists Links to related material The MOOC related to this book is accessible via the "Online Course" link at algs4.cs.princeton.edu. The course offers more than 100 video lecture segments that are integrated with the text, extensive online assessments, and the large-scale discussion forums that have proven so valuable. Offered each fall and spring, this course regularly attracts tens of thousands of registrants. Robert Sedgewick and Kevin Wayne are developing a modern approach to disseminating knowledge that fully embraces technology, enabling people all around the world to discover new ways of learning and teaching. By integrating their textbook, online content, and MOOC, all at the state of the art, they have built a unique resource that greatly expands the breadth and depth of the educational experience.
Preis: 20.32 € | Versand*: 0 € -
Algorithms: Part I
This book is Part I of the fourth edition of Robert Sedgewick and Kevin Wayne’s Algorithms, the leading textbook on algorithms today, widely used in colleges and universities worldwide. Part I contains Chapters 1 through 3 of the book. The fourth edition of Algorithms surveys the most important computer algorithms currently in use and provides a full treatment of data structures and algorithms for sorting, searching, graph processing, and string processing -- including fifty algorithms every programmer should know. In this edition, new Java implementations are written in an accessible modular programming style, where all of the code is exposed to the reader and ready to use. The algorithms in this book represent a body of knowledge developed over the last 50 years that has become indispensable, not just for professional programmers and computer science students but for any student with interests in science, mathematics, and engineering, not to mention students who use computation in the liberal arts. The companion web site, algs4.cs.princeton.edu contains An online synopsis Full Java implementations Test data Exercises and answers Dynamic visualizations Lecture slides Programming assignments with checklists Links to related material The MOOC related to this book is accessible via the "Online Course" link at algs4.cs.princeton.edu. The course offers more than 100 video lecture segments that are integrated with the text, extensive online assessments, and the large-scale discussion forums that have proven so valuable. Offered each fall and spring, this course regularly attracts tens of thousands of registrants. Robert Sedgewick and Kevin Wayne are developing a modern approach to disseminating knowledge that fully embraces technology, enabling people all around the world to discover new ways of learning and teaching. By integrating their textbook, online content, and MOOC, all at the state of the art, they have built a unique resource that greatly expands the breadth and depth of the educational experience.
Preis: 20.32 € | Versand*: 0 €
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Warum ist "For Honor" weiblich?
"For Honor" ist ein Videospiel, das von Ubisoft entwickelt wurde. Der Name des Spiels wurde vermutlich gewählt, um die Idee von Ehre und Tapferkeit zu vermitteln, die im Spiel eine wichtige Rolle spielen. Die Verwendung des weiblichen Geschlechts für den Namen des Spiels könnte darauf hinweisen, dass Frauen genauso fähig sind, Ehre und Tapferkeit zu verkörpern wie Männer.
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Wie funktionieren Iterationsverfahren zur numerischen Lösung von Gleichungssystemen? Welche Vor- und Nachteile haben verschiedene Iterationsverfahren bei der Approximation von Nullstellen von Funktionen?
Iterationsverfahren zur numerischen Lösung von Gleichungssystemen wiederholen einen Prozess, um eine Näherungslösung zu finden, indem sie eine Startschätzung verwenden und sie iterativ verbessern. Dabei wird die Konvergenzrate und Genauigkeit des Verfahrens durch die Wahl des Iterationsverfahrens beeinflusst. Ein Vorteil von Iterationsverfahren ist, dass sie oft schneller sind als direkte Lösungsmethoden, aber ein Nachteil ist, dass sie möglicherweise nicht immer konvergieren oder instabil werden können.
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Welcher Kindersitz Smart For Two?
Welcher Kindersitz ist für den Smart For Two geeignet? Es gibt spezielle Kindersitze, die speziell für den Smart For Two entwickelt wurden und perfekt in das Fahrzeug passen. Es ist wichtig, einen Kindersitz zu wählen, der den Sicherheitsstandards entspricht und optimalen Schutz für das Kind bietet. Beim Kauf eines Kindersitzes für den Smart For Two sollte darauf geachtet werden, dass er einfach zu installieren und zu bedienen ist. Außerdem sollte der Kindersitz je nach Alter, Größe und Gewicht des Kindes ausgewählt werden, um die bestmögliche Sicherheit zu gewährleisten.
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Wie kann man eine Funktion durch eine Polynomapproximation annähern? Welche Anwendungsbereiche hat die Approximation in der Mathematik und Physik?
Man kann eine Funktion durch eine Polynomapproximation annähern, indem man die Funktion durch ein Polynom niedrigeren Grades ersetzt, das die Funktion möglichst gut annähert. Diese Approximation wird oft in der numerischen Mathematik verwendet, um komplexe Funktionen zu vereinfachen und Berechnungen zu vereinfachen. In der Physik wird die Polynomapproximation verwendet, um komplexe physikalische Phänomene zu modellieren und zu verstehen.
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