Using Graphs

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Graphs Don T Lie

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Author : Lee Baker
language : en
Publisher: Lee Baker
Release Date :

Graphs Don T Lie written by Lee Baker and has been published by Lee Baker this book supported file pdf, txt, epub, kindle and other format this book has been release on with Education categories.

Sarah Palin, abortions, global warming and Usain Bolt. The CEO of Apple, 35 trillion gun deaths in 1995, Fox News and 193%. This book has got scandals galore! With 9 witty chapters taking you on a roller coaster tour of graphical lies, pictorial deceits and pie charts of mayhem, this might just be the most entertaining book about graphs you’ll read this year. Did you know that between them, Sarah Palin, Mike Huckabee and Mitt Romney enjoyed a total of 193% support from Republican candidates in the 2012 US primaries? It must be true – it was on a pie chart broadcast on Fox News. Did you also know that the number 34 is smaller than 14, and zero is much bigger than 22? Honest, it’s true, it was published in a respectable national newspaper after the 2017 UK General Election. There can’t have been any kind of misdirection here because they were all shown on a pie chart. In this astonishing book, award winning statistician and author Lee Baker uncovers how politicians, the press, corporations and other statistical conmen use graphs and charts to deceive their unwitting audience. Like how a shocking, and yet seemingly innocuous statement as “Every year since 1950, the number of children gunned down has doubled”, meant that there should have been at least 35 trillion gun deaths in 1995 alone, the year the quote was printed in a reputable journal. Or how an anti-abortion group made their point by trying to convince us all that 327,000 is actually a larger number than 935,573. Nice try, but no cigar – we weren’t born yesterday. In his trademark sardonic style, the author reveals the secrets of how the statistical hustlers use graphs and charts to manipulate and misrepresent for political or commercial gain – and often get away with it. Written as a layman’s guide to lying, cheating and deceiving with graphs, there’s not a dull page in sight! And it’s got elephants in it too… Discover the exciting world of lying with graphs and charts. Get this book, TODAY!

Using Graphs

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Author : Julie Ellis
language : en
Publisher: Flying Start Books
Release Date : 2021-04-30

Using Graphs written by Julie Ellis and has been published by Flying Start Books this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-30 with Juvenile Nonfiction categories.

A graph is a picture or chart showing the differences between things that we can measure. It helps us to understand information when we can see the facts in a picture. We use different kinds of graphs to show different kinds of information.

Using Charts And Graphs

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Author : Jan V. White
language : en
Publisher: Libraries Unltd Incorporated
Release Date : 1984-01

Using Charts And Graphs written by Jan V. White and has been published by Libraries Unltd Incorporated this book supported file pdf, txt, epub, kindle and other format this book has been release on 1984-01 with Language Arts & Disciplines categories.

Explains the purpose of diagrams, pie charts, bar graphs, dot charts, flow charts, maps, and tables, demonstrates chart making techniques, and shows how to combine different kinds of charts

Human Interaction With Graphs

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Author : Sourav S. Bhowmick
language : en
Publisher: Springer Nature
Release Date : 2022-06-01

Human Interaction With Graphs written by Sourav S. Bhowmick and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.

Interacting with graphs using queries has emerged as an important research problem for real-world applications that center on large graph data. Given the syntactic complexity of graph query languages (e.g., SPARQL, Cypher), visual graph query interfaces make it easy for non-programmers to query such graph data repositories. In this book, we present recent developments in the emerging area of visual graph querying paradigm that bridges traditional graph querying with human computer interaction (HCI). Specifically, we focus on techniques that emphasize deep integration between the visual graph query interface and the underlying graph query engine. We discuss various strategies and guidance for constructing graph queries visually, interleaving processing of graph queries and visual actions, visual exploration of graph query results, and automated performance study of visual graph querying frameworks. In addition, this book highlights open problems and new research directions. In summary, in this book, we review and summarize the research thus far into the integration of HCI and graph querying to facilitate user-friendly interaction with graph-structured data, giving researchers a snapshot of the current state of the art in this topic, and future research directions.

Using Graphs Us Edition Readaloud

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Author : Julie Ellis
language : en
Publisher: Flying Start Books
Release Date : 2021-04-30

Using Graphs Us Edition Readaloud written by Julie Ellis and has been published by Flying Start Books this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-30 with Juvenile Nonfiction categories.

A graph is a picture or chart showing the differences between things that we can measure. It helps us to understand information when we can see the facts in a picture. We use different kinds of graphs to show different kinds of information.

Making And Using Graphs Set

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Author :
language : en
Publisher:
Release Date : 2013

Making And Using Graphs Set written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.

Making and Using Graphs employs bright illustrations and clear text to teach young readers how to create and use graphs to represent and analyze data. Five books in the series each introduce a single type of graph and offer examples, as well as activities designed for readers to practice gathering and graphing data. A conclusion summarizes key concepts and suggests more graphing activities. The sixth book focuses on a variety of graph types, introducing them as tools for readers to use to solve story problems.

Graph Algorithms For Data Science

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Author : Tomaž Bratanic
language : en
Publisher: Simon and Schuster
Release Date : 2024-03-12

Graph Algorithms For Data Science written by Tomaž Bratanic and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-12 with Computers categories.

Practical methods for analyzing your data with graphs, revealing hidden connections and new insights. Graphs are the natural way to represent and understand connected data. This book explores the most important algorithms and techniques for graphs in data science, with concrete advice on implementation and deployment. 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. In Graph Algorithms for Data Science you will learn: Labeled-property graph modeling Constructing a graph from structured data such as CSV or SQL NLP techniques to construct a graph from unstructured data Cypher query language syntax to manipulate data and extract insights Social network analysis algorithms like PageRank and community detection How to translate graph structure to a ML model input with node embedding models Using graph features in node classification and link prediction workflows Graph 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. Foreword by Michael Hunger. About the technology A graph, put simply, is a network of connected data. Graphs are an efficient way to identify and explore the significant relationships naturally occurring within a dataset. This book presents the most important algorithms for graph data science with examples from machine learning, business applications, natural language processing, and more. About the book Graph Algorithms for Data Science shows you how to construct and analyze graphs from structured and unstructured data. In it, you’ll learn to apply graph algorithms like PageRank, community detection/clustering, and knowledge graph models by putting each new algorithm to work in a hands-on data project. This cutting-edge book also demonstrates how you can create graphs that optimize input for AI models using node embedding. What's inside Creating knowledge graphs Node classification and link prediction workflows NLP techniques for graph construction About the reader For data scientists who know machine learning basics. Examples use the Cypher query language, which is explained in the book. About the author Tomaž Bratanic works at the intersection of graphs and machine learning. Arturo Geigel was the technical editor for this book. Table of Contents PART 1 INTRODUCTION TO GRAPHS 1 Graphs and network science: An introduction 2 Representing network structure: Designing your first graph model PART 2 SOCIAL NETWORK ANALYSIS 3 Your first steps with Cypher query language 4 Exploratory graph analysis 5 Introduction to social network analysis 6 Projecting monopartite networks 7 Inferring co-occurrence networks based on bipartite networks 8 Constructing a nearest neighbor similarity network PART 3 GRAPH MACHINE LEARNING 9 Node embeddings and classification 10 Link prediction 11 Knowledge graph completion 12 Constructing a graph using natural language processing technique

Using Graphs

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Author : Tom Yager
language : en
Publisher: Milliken Publishing Company
Release Date : 2000-09-01

Using Graphs written by Tom Yager and has been published by Milliken Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-09-01 with Education categories.

This book helps students learn about many types of tables and graphs, as well as how to use and compare the data contained in various graphs. These pages may be assigned as a class lesson, individual seat work, or homework activities. Answer key is included.

Presenting Statistics Using Graphs Charts And Tables

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Author :
language : en
Publisher:
Release Date : 1988

Presenting Statistics Using Graphs Charts And Tables written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Graphic methods categories.

Graph Powered Machine Learning

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Author : Alessandro Negro
language : en
Publisher: Simon and Schuster
Release Date : 2021-10-05

Graph Powered Machine Learning written by Alessandro Negro and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-05 with Computers categories.

Upgrade your machine learning models with graph-based algorithms, the perfect structure for complex and interlinked data. Summary In Graph-Powered Machine Learning, you will learn: The lifecycle of a machine learning project Graphs in big data platforms Data source modeling using graphs Graph-based natural language processing, recommendations, and fraud detection techniques Graph algorithms Working with Neo4J Graph-Powered Machine Learning teaches to use graph-based algorithms and data organization strategies to develop superior machine learning applications. You’ll dive into the role of graphs in machine learning and big data platforms, and take an in-depth look at data source modeling, algorithm design, recommendations, and fraud detection. Explore end-to-end projects that illustrate architectures and help you optimize with best design practices. Author Alessandro Negro’s extensive experience shines through in every chapter, as you learn from examples and concrete scenarios based on his work with real clients! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Identifying relationships is the foundation of machine learning. By recognizing and analyzing the connections in your data, graph-centric algorithms like K-nearest neighbor or PageRank radically improve the effectiveness of ML applications. Graph-based machine learning techniques offer a powerful new perspective for machine learning in social networking, fraud detection, natural language processing, and recommendation systems. About the book Graph-Powered Machine Learning teaches you how to exploit the natural relationships in structured and unstructured datasets using graph-oriented machine learning algorithms and tools. In this authoritative book, you’ll master the architectures and design practices of graphs, and avoid common pitfalls. Author Alessandro Negro explores examples from real-world applications that connect GraphML concepts to real world tasks. What's inside Graphs in big data platforms Recommendations, natural language processing, fraud detection Graph algorithms Working with the Neo4J graph database About the reader For readers comfortable with machine learning basics. About the author Alessandro Negro is Chief Scientist at GraphAware. He has been a speaker at many conferences, and holds a PhD in Computer Science. Table of Contents PART 1 INTRODUCTION 1 Machine learning and graphs: An introduction 2 Graph data engineering 3 Graphs in machine learning applications PART 2 RECOMMENDATIONS 4 Content-based recommendations 5 Collaborative filtering 6 Session-based recommendations 7 Context-aware and hybrid recommendations PART 3 FIGHTING FRAUD 8 Basic approaches to graph-powered fraud detection 9 Proximity-based algorithms 10 Social network analysis against fraud PART 4 TAMING TEXT WITH GRAPHS 11 Graph-based natural language processing 12 Knowledge graphs