Products related to Graph:
-
Graph Learning Techniques
This comprehensive guide addresses key challenges at the intersection of data science, graph learning, and privacy preservation.It begins with foundational graph theory, covering essential definitions, concepts, and var-ious types of graphs.The book bridges the gap between theory and application, equipping readers with the skills to translate theoretical knowledge into actionable solutions for complex problems.It includes practical insights into brain network analysis and the dynamics of COVID-19 spread.The guide provides a solid understanding of graphs by exploring different graph representations and the latest advancements in graph learning techniques.It focuses on diverse graph signals and offers a detailed review of state-of-the-art methodologies for analyzing these signals.A major emphasis is placed on privacy preservation, with comprehensive discussions on safeguarding sensitive information within graph structures.The book also looks forward, offering insights into emerging trends, potential challenges, and the evolving landscape of privacy-preserving graph learning.This resource is a valuable reference for advance undergraduate and postgraduate students in courses related to Network Analysis, Privacy and Security in Data Analytics, and Graph Theory and Applications in Healthcare.
Price: 44.99 £ | Shipping*: 0.00 £ -
Graph-Powered Machine Learning
At its core, machine learning is about efficiently identifying patterns and relationships in data.Many tasks, such as finding associations among terms so you can make accurate search recommendations or locating individuals within a social network who have similar interests, are naturally expressed as graphs. Graph-Powered Machine Learning introduces you to graph technology concepts, highlighting the role of graphs in machine learning and big data platforms.You’ll get an in-depth look at techniques including data source modeling, algorithm design, link analysis, classification, and clustering.As you master the core concepts, you’ll explore three end-to-end projects that illustrate architectures, best design practices, optimization approaches, and common pitfalls. Key Features · The lifecycle of a machine learning project · Three end-to-end applications · Graphs in big data platforms · Data source modeling · Natural language processing, recommendations, and relevant search · Optimization methods Readers comfortable with machine learning basics. About the technology By organizing and analyzing your data as graphs, your applications work more fluidly with graph-centric algorithms like nearest neighbor or page rank where it’s important to quickly identify and exploit relevant relationships.Modern graph data stores, like Neo4j or Amazon Neptune, are readily available tools that support graph-powered machine learning. Alessandro Negro is a Chief Scientist at GraphAware.With extensive experience in software development, software architecture, and data management, he has been a speaker at many conferences, such as Java One, Oracle Open World, and Graph Connect.He holds a Ph.D. in Computer Science and has authored several publications on graph-based machine learning.
Price: 47.99 £ | Shipping*: 0.00 £ -
Teaching, Tutoring and Training in the Lifelong Learning Sector
This core text provides comprehensive support for pre-service and in-service trainee teachers in the Lifelong Learning Sector covering all they need to know to achieve QTLS status. Supporting trainees through all stages of their professional development, the text takes the reader through the theoretical background underpinning teaching and learning and offers practical guidance on day-to-day challenges. This fourth edition has been fully revised and updated and includes a new chapter on teaching practice with notes on observation and lesson planning.New information on behaviour management has been added to support trainees in an aspect of teaching that many find challenging.
Price: 36.99 £ | Shipping*: 0.00 £ -
Graph Theory
This standard textbook on modern graph theory combines the authority of a classic with the engaging freshness of style that is the hallmark of active mathematics.It covers the core material of the subject, with concise yet complete proofs, while offering glimpses of more advanced methods in each field via one or two deeper results. This is a major new edition. Among many other improvements, it offers additional tools for applying the regularity lemma, brings the tangle theory of graph minors up to the cutting edge of current research, and addresses new topics such as chi-boundedness in perfect graph theory. The book can be used as a reliable text for an introductory graduate course and is also suitable for self-study. From the reviews:“Deep, clear, wonderful. This is a serious book about the heart of graph theory.It has depth and integrity.” Persi Diaconis & Ron Graham, SIAM Review“The book has received a very enthusiastic reception, which it amply deserves.A masterly elucidation of modern graph theory.” Bulletin of the Institute of Combinatorics and its Applications“Succeeds dramatically ... a hell of a good book.” MAA Reviews“ ... like listening to someone explain mathematics.” Bulletin of the AMS
Price: 54.99 £ | Shipping*: 0.00 £
-
Which graph is the graph of f?
The graph of f is the second graph, which is a parabola that opens upward. This can be determined because the function f(x) = ax^2 + bx + c is a quadratic function, and the second graph is a parabola, which is the graph of a quadratic function. Additionally, the fact that the parabola opens upward indicates that the coefficient a in the function f(x) = ax^2 + bx + c is positive. Therefore, the second graph is the graph of f.
-
How do you graph a graph with fractions?
To graph a graph with fractions, you can start by plotting the x and y intercepts. If the fractions are in the form of y = mx + b, where m is the slope and b is the y-intercept, you can plot the y-intercept at the point (0, b). Then, use the slope to find another point on the line by moving up or down based on the numerator of the fraction and left or right based on the denominator. Connect the two points to create the line. If the fractions are in the form of y = ax^2 + bx + c, you can use the x-intercepts and vertex to plot the graph.
-
What is a bar graph elementary school?
A bar graph is a type of chart that uses bars to represent data. In an elementary school setting, a bar graph is often used to visually display information in a simple and easy-to-understand way. Students can use bar graphs to compare different categories or groups of data, such as the number of students in each grade level or the favorite colors of their classmates. This visual representation helps students develop their data interpretation and analysis skills.
-
How can one recognize the function graph from the derivative graph?
To recognize the function graph from the derivative graph, one can look for key features such as peaks and valleys in the derivative graph, which correspond to zeros or extrema in the function graph. Additionally, the derivative graph crossing the x-axis indicates where the function graph has a maximum or minimum point. The derivative graph also helps identify where the function graph is increasing or decreasing by observing the positive or negative values of the derivative. By analyzing these features, one can infer the behavior and shape of the original function graph.
Similar search terms for Graph:
-
Graph Sampling
Many technological, socio-economic, environmental, biomedical phenomena exhibit an underlying graph structure.Valued graph allows one to incorporate the connections or links among the population units in addition.The links may provide effectively access to the part of population that is the primary target, which is the case for many unconventional sampling methods, such as indirect, network, line-intercept or adaptive cluster sampling. Or, one may be interested in the structure of the connections, in terms of the corresponding graph properties or parameters, such as when various breadth- or depth-first non-exhaustive search algorithms are applied to obtain compressed views of large often dynamic graphs.Graph sampling provides a statistical approach to study real graphs from either of these perspectives.It is based on exploring the variation over all possible sample graphs (or subgraphs) which can be taken from the given population graph, by means of the relevant known sampling probabilities.The resulting design-based inference is valid whatever the unknown properties of the given real graphs. One-of-a-kind treatise of multidisciplinary topics relevant to statistics, mathematics and data science. Probabilistic treatment of breadth-first and depth-first non-exhaustive search algorithms in graphs. Presenting cutting-edge theory and methods based on latest research. Pathfinding for future research on sampling from real graphs. Graph Sampling can primarily be used as a resource for researchers working with sampling or graph problems, and as the basis of an advanced course for post-graduate students in statistics, mathematics and data science.
Price: 49.99 £ | Shipping*: 0.00 £ -
Graph Learning and Network Science for Natural Language Processing
Advances in graph-based natural language processing (NLP) and information retrieval tasks have shown the importance of processing using the Graph of Words method.This book covers recent concrete information, from the basics to advanced level, about graph-based learning, such as neural network-based approaches, computational intelligence for learning parameters and feature reduction, and network science for graph-based NPL.It also contains information about language generation based on graphical theories and language models. Features:Presents a comprehensive study of the interdisciplinary graphical approach to NLPCovers recent computational intelligence techniques for graph-based neural network modelsDiscusses advances in random walk-based techniques, semantic webs, and lexical networksExplores recent research into NLP for graph-based streaming dataReviews advances in knowledge graph embedding and ontologies for NLP approachesThis book is aimed at researchers and graduate students in computer science, natural language processing, and deep and machine learning.
Price: 105.00 £ | Shipping*: 0.00 £ -
Computer Science Education : Perspectives on Teaching and Learning in School
Drawing together the most up-to-date research from experts all across the world, the second edition of Computer Science Education offers the most up-to-date coverage available on this developing subject, ideal for building confidence of new pre-service and in-service educators teaching a new discipline.It provides an international overview of key concepts, pedagogical approaches and assessment practices. Highlights of the second edition include:- New sections on machine learning and data-driven (epistemic) programming- A new focus on equity and inclusion in computer science education- Chapters updated throughout, including a revised chapter on relating ethical and societal aspects to knowledge-rich aspects of computer science education- A new set of chapters on the learning of programming, including design, pedagogy and misconceptions- A chapter on the way we use language in the computer science classroom. The book is structured to support the reader with chapter outlines, synopses and key points.Explanations of key concepts, real-life examples and reflective points keep the theory grounded in classroom practice. The book is accompanied by a companion website, including online summaries for each chapter, 3-minute video summaries by each author and an archived chapter on taxonomies and competencies from the first edition.
Price: 26.99 £ | Shipping*: 3.99 £ -
The Practitioner's Guide to Graph Data : Applying Graph Thinking and Graph Technologies to Solve Complex Problems
Graph data closes the gap between the way humans and computers view the world.While computers rely on static rows and columns of data, people navigate and reason about life through relationships.This practical guide demonstrates how graph data brings these two approaches together.By working with concepts from graph theory, database schema, distributed systems, and data analysis, you'll arrive at a unique intersection known as graph thinking. Authors Denise Koessler Gosnell and Matthias Broecheler show data engineers, data scientists, and data analysts how to solve complex problems with graph databases.You'll explore templates for building with graph technology, along with examples that demonstrate how teams think about graph data within an application. Build an example application architecture with relational and graph technologiesUse graph technology to build a Customer 360 application, the most popular graph data pattern todayDive into hierarchical data and troubleshoot a new paradigm that comes from working with graph dataFind paths in graph data and learn why your trust in different paths motivates and informs your preferencesUse collaborative filtering to design a Netflix-inspired recommendation system
Price: 63.99 £ | Shipping*: 0.00 £
-
What is the English translation for 'graph stretching' and 'graph compressing'?
The English translation for 'graph stretching' is to increase the size or scale of a graph, making it appear larger or more spread out. On the other hand, 'graph compressing' refers to reducing the size or scale of a graph, making it appear smaller or more condensed. These terms are commonly used in mathematics and data visualization to describe the manipulation of the dimensions of a graph.
-
What is a graph?
A graph is a mathematical structure that consists of a set of vertices (nodes) connected by edges (links). It is used to represent relationships between different entities. Graphs are widely used in various fields such as computer science, social networks, transportation systems, and biology to model and analyze complex systems. They can be directed (edges have a specific direction) or undirected (edges have no specific direction).
-
How do you graph the graph of a rational function in mathematics?
To graph a rational function, first identify the vertical and horizontal asymptotes by finding the values that make the denominator equal to zero and the degree of the numerator and denominator. Then, find the x-intercepts by setting the numerator equal to zero. Next, determine the behavior of the function near the asymptotes and x-intercepts. Finally, plot the points and sketch the graph, making sure to show the behavior near the asymptotes and x-intercepts.
-
Can you draw a graph on the GTR using only the graph?
No, I cannot draw a graph on the GTR using only the graph. The GTR (Graphing Calculator) is a tool that allows users to input equations and functions to generate graphs. It does not have the capability to interpret a graph and create an equation or function from it. In order to create a graph on the GTR, you would need to input the equation or function that corresponds to the graph you want to see.
* All prices are inclusive of VAT and, if applicable, plus shipping costs. The offer information is based on the details provided by the respective shop and is updated through automated processes. Real-time updates do not occur, so deviations can occur in individual cases.