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data ecosystems --- data fusion --- data mapping --- data visualisation --- Machine learning --- Machine learning. --- Learning, Machine --- Artificial intelligence --- Machine theory --- Apprentissage automatique
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"Business intelligence software has rapidly spread its roots in the AEC industry during the last few years. This has happened due to the presence of rich digital data in BIM models whose datasets can be gathered, organized, and visualized through software such as Autodesk Dynamo BIM and Power BI. Managing and Visualizing Your BIM Data helps you understand and implement computer science fundamentals to better absorb the process of creating Dynamo scripts and visualizing the collected data on powerful dashboards. This book provides a hands-on approach and associated methodologies that will have you productive and up and running in no time. After understanding the theoretical aspects of computer science and related topics, you will focus on Autodesk Dynamo to develop scripts to manage data. Later, the book demonstrates four case studies from AEC experts across the world. In this section, you'll learn how to get started with Autodesk Dynamo to gather data from a Revit model and create a simple C# plugin for Revit to stream data on Power BI directly. As you progress, you'll explore how to create dynamic Power BI dashboards using Revit floor plans and make a Power BI dashboard to track model issues. By the end of this book, you'll have learned how to develop a script to gather a model's data and visualize datasets in Power BI easily." [Back cover] "Le logiciel de Business Intelligence a rapidement étendu ses racines dans l'industrie de l'AEC au cours des dernières années. Cela s'est produit en raison de la présence de données numériques riches dans les modèles BIM dont les ensembles de données peuvent être rassemblés, organisés et visualisés via des logiciels tels que Autodesk Dynamo BIM et Power BI. La gestion et la visualisation de vos données BIM vous aident à comprendre et à mettre en œuvre les principes fondamentaux de l'informatique afin de mieux absorber le processus de création de scripts Dynamo et de visualiser les données collectées sur des tableaux de bord puissants. Ce livre propose une approche pratique et des méthodologies associées qui vous permettront d'être productif et opérationnel en un rien de temps. Après avoir compris les aspects théoriques de l'informatique et des sujets connexes, vous vous concentrerez sur Autodesk Dynamo pour développer des scripts de gestion des données. Plus tard, le livre présente quatre études de cas d'experts de l'AEC à travers le monde. Dans cette section, vous apprendrez comment démarrer avec Autodesk Dynamo pour collecter des données à partir d'un modèle Revit et créer un simple plug-in C# pour Revit afin de diffuser des données directement sur Power BI. Au fur et à mesure de votre progression, vous découvrirez comment créer des tableaux de bord Power BI dynamiques à l'aide de plans d'étage Revit et créer un tableau de bord Power BI pour suivre les problèmes de modèle. À la fin de ce livre, vous aurez appris à développer un script pour rassembler les données d'un modèle et visualiser facilement des ensembles de données dans Power BI." [Traduction de la 4ème de couverture]
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This open access book represents one of the key milestones of PoliVisu, an H2020 research and innovation project funded by the European Commission under the call “Policy-development in the age of big data: data-driven policy-making, policy-modelling and policy-implementation”. It investigates the operative and organizational implications related to the use of the growing amount of available data on policy making processes, highlighting the experimental dimension of policy making that, thanks to data, proves to be more and more exploitable towards more effective and sustainable decisions. The first section of the book introduces the key questions highlighted by the PoliVisu project, which still represent operational and strategic challenges in the exploitation of data potentials in urban policy making. The second section explores how data and data visualisations can assume different roles in the different stages of a policy cycle and profoundly transform policy making.
Urban & municipal planning --- Sociology --- Public administration --- Urban Geography / Urbanism (inc. megacities, cities, towns) --- Urban Studies/Sociology --- Public Policy --- Urban Geography and Urbanism --- Urban Sociology --- Urban Policy --- Urban mobility --- Data visualisation --- public policy making --- policy making processes --- smart city --- POLIVISU project --- urban data --- open access --- Urban communities
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Computational Biology --- Bio-Informatics --- Biology, Computational --- Computational Molecular Biology --- Bioinformatics --- Molecular Biology, Computational --- Bio Informatics --- Bio-Informatic --- Bioinformatic --- Biologies, Computational Molecular --- Biology, Computational Molecular --- Computational Molecular Biologies --- Molecular Biologies, Computational --- Computational Chemistry --- Genomics --- data visualisation --- integrative bioinformatics --- genomics --- computational bioimaging --- Computational Biology.
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Over 70 recipes to get you started with popular Python libraries based on the principal concepts of data visualization About This Book Learn how to set up an optimal Python environment for data visualization Understand how to import, clean and organize your data Determine different approaches to data visualization and how to choose the most appropriate for your needs Who This Book Is For If you already know about Python programming and want to understand data, data formats, data visualization, and how to use Python to visualize data then this book is for you. What You Will Learn Introduce yourself to the essential tooling to set up your working environment Explore your data using the capabilities of standard Python Data Library and Panda Library Draw your first chart and customize it Use the most popular data visualization Python libraries Make 3D visualizations mainly using mplot3d Create charts with images and maps Understand the most appropriate charts to describe your data Know the matplotlib hidden gems Use plot.ly to share your visualization online In Detail Python Data Visualization Cookbook will progress the reader from the point of installing and setting up a Python environment for data manipulation and visualization all the way to 3D animations using Python libraries. Readers will benefit from over 60 precise and reproducible recipes that will guide the reader towards a better understanding of data concepts and the building blocks for subsequent and sometimes more advanced concepts. Python Data Visualization Cookbook starts by showing how to set up matplotlib and the related libraries that are required for most parts of the book, before moving on to discuss some of the lesser-used diagrams and charts such as Gantt Charts or Sankey diagrams. Initially it uses simple plots and charts to more advanced ones, to make it easy to understand for readers. As the readers will go through the book, they will get to know about the 3D diagrams and animations. Maps are irreplaceable for displaying geo-spatial data, so this book will also show how to build them. In the last chapter, it includes explanation on how to incorporate matplotlib into different environments, such as a writing system, LaTeX, or how to create Gantt charts using Python. Style and approach A step-by-step recipe based approach to data visualization. The topics are explained sequentially as cookbook recipes consisting of a code snippet and the resulting visualization.
Information visualization --- Python (Computer program language) --- Python (langage de programmation) --- Database management. --- Data structures (Computer science) --- Information structures (Computer science) --- Structures, Data (Computer science) --- Structures, Information (Computer science) --- Electronic data processing --- File organization (Computer science) --- Abstract data types (Computer science) --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management --- Scripting languages (Computer science) --- Information visualization. --- Data visualisation.
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This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas.
Artificial intelligence. --- Big data. --- Data sets, Large --- Large data sets --- Data sets --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Big Data --- Data Management --- Data Processing --- Data Analytics --- Data Visualisation and User Interaction --- Knowledge Discovery --- Information Retrieval --- Dades massives --- Intel·ligència artificial
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