From Data To Models And Back

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From Data to Models and Back

Juliana Bowles,Giovanna Broccia,Roberto Pellungrini
From Data to Models and Back Book PDF

Author : Juliana Bowles,Giovanna Broccia,Roberto Pellungrini
Publisher : Springer Nature
Page : 199 pages
File Size : 41,9 Mb
Release : 2022-10-14
Category : Computers
ISBN : 9783031160110

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From Data to Models and Back by Juliana Bowles,Giovanna Broccia,Roberto Pellungrini Pdf

This book constitutes the refereed proceedings of the 10th International Symposium "From Data Models and Back", DataMod 2021, which was held virtually during December 6-7, 2021, as a satellite event of SEFM 2021. The 9 full papers and 1 short paper included in this book were carefully reviewed and selected from 12 submissions. They were organized in topical sections as follows: Model verification; data mining and processing related approaches; and other approaches.

R for Data Science

Hadley Wickham,Garrett Grolemund
R for Data Science Book PDF

Author : Hadley Wickham,Garrett Grolemund
Publisher : "O'Reilly Media, Inc."
Page : 521 pages
File Size : 52,6 Mb
Release : 2016-12-12
Category : Computers
ISBN : 9781491910368

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R for Data Science by Hadley Wickham,Garrett Grolemund Pdf

Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

From Data to Models and Back

Juliana Bowles,Giovanna Broccia,Mirco Nanni
From Data to Models and Back Book PDF

Author : Juliana Bowles,Giovanna Broccia,Mirco Nanni
Publisher : Unknown
Page : 0 pages
File Size : 50,9 Mb
Release : 2021
Category : Electronic
ISBN : 3030706516

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From Data to Models and Back by Juliana Bowles,Giovanna Broccia,Mirco Nanni Pdf

This book constitutes the refereed proceedings of the 9th International Symposium on From Data Models and Back, DataMod 2020, held virtually, in October 2020. The 11 full papers and 3 short papers presented in this book were selected from 19 submissions. The papers are grouped in these topical sections: machine learning; simulation-based approaches, and data mining and processing related approaches.

Developing High Quality Data Models

Matthew West
Developing High Quality Data Models Book PDF

Author : Matthew West
Publisher : Elsevier
Page : 408 pages
File Size : 43,5 Mb
Release : 2011-02-07
Category : Computers
ISBN : 0123751071

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Developing High Quality Data Models by Matthew West Pdf

Developing High Quality Data Models provides an introduction to the key principles of data modeling. It explains the purpose of data models in both developing an Enterprise Architecture and in supporting Information Quality; common problems in data model development; and how to develop high quality data models, in particular conceptual, integration, and enterprise data models. The book is organized into four parts. Part 1 provides an overview of data models and data modeling including the basics of data model notation; types and uses of data models; and the place of data models in enterprise architecture. Part 2 introduces some general principles for data models, including principles for developing ontologically based data models; and applications of the principles for attributes, relationship types, and entity types. Part 3 presents an ontological framework for developing consistent data models. Part 4 provides the full data model that has been in development throughout the book. The model was created using Jotne EPM Technologys EDMVisualExpress data modeling tool. This book was designed for all types of modelers: from those who understand data modeling basics but are just starting to learn about data modeling in practice, through to experienced data modelers seeking to expand their knowledge and skills and solve some of the more challenging problems of data modeling. Uses a number of common data model patterns to explain how to develop data models over a wide scope in a way that is consistent and of high quality Offers generic data model templates that are reusable in many applications and are fundamental for developing more specific templates Develops ideas for creating consistent approaches to high quality data models

The Data Model Resource Book, Volume 1

Len Silverston
The Data Model Resource Book Volume 1 Book PDF

Author : Len Silverston
Publisher : John Wiley & Sons
Page : 572 pages
File Size : 41,5 Mb
Release : 2011-08-08
Category : Computers
ISBN : 9781118082324

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The Data Model Resource Book, Volume 1 by Len Silverston Pdf

A quick and reliable way to build proven databases for core business functions Industry experts raved about The Data Model Resource Book when it was first published in March 1997 because it provided a simple, cost-effective way to design databases for core business functions. Len Silverston has now revised and updated the hugely successful 1st Edition, while adding a companion volume to take care of more specific requirements of different businesses. This updated volume provides a common set of data models for specific core functions shared by most businesses like human resources management, accounting, and project management. These models are standardized and are easily replicated by developers looking for ways to make corporate database development more efficient and cost effective. This guide is the perfect complement to The Data Model Resource CD-ROM, which is sold separately and provides the powerful design templates discussed in the book in a ready-to-use electronic format. A free demonstration CD-ROM is available with each copy of the print book to allow you to try before you buy the full CD-ROM.

Data Analysis Using Regression and Multilevel/Hierarchical Models

Andrew Gelman,Jennifer Hill
Data Analysis Using Regression and Multilevel Hierarchical Models Book PDF

Author : Andrew Gelman,Jennifer Hill
Publisher : Cambridge University Press
Page : 654 pages
File Size : 43,6 Mb
Release : 2007
Category : Mathematics
ISBN : 052168689X

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Data Analysis Using Regression and Multilevel/Hierarchical Models by Andrew Gelman,Jennifer Hill Pdf

This book, first published in 2007, is for the applied researcher performing data analysis using linear and nonlinear regression and multilevel models.

Microsoft Excel 2013 Building Data Models with PowerPivot

Alberto Ferrari,Marco Russo
Microsoft Excel 2013 Building Data Models with PowerPivot Book PDF

Author : Alberto Ferrari,Marco Russo
Publisher : Pearson Education
Page : 511 pages
File Size : 43,8 Mb
Release : 2013-03-15
Category : Computers
ISBN : 9780735676565

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Microsoft Excel 2013 Building Data Models with PowerPivot by Alberto Ferrari,Marco Russo Pdf

Your guide to quickly turn data into results. Transform your skills, data, and business—and create your own BI solutions using software you already know and love: Microsoft Excel. Two business intelligence (BI) experts take you inside PowerPivot functionality for Excel 2013, with a focus on real world scenarios, problem-solving, and data modeling. You'll learn how to quickly turn mass quantities of data into meaningful information and on-the-job results—no programming required! Understand the differences between PowerPivot for Self Service BI and SQL Server Analysis Services for Corporate BI Extend your existing data-analysis skills to create your own BI solutions Quickly manipulate large data sets, often in millions of rows Perform simple-to-sophisticated calculations and what-if analysis Create complex reporting systems with data modeling and Data Analysis Expressions Share your results effortlessly across your organization using Microsoft SharePoint Authors’ note on using Microsoft Excel 2016: This book’s content was written against Excel 2013, but it is useful and valid for users of Excel 2016 too. Excel 2016 introduces several new DAX functions and an improved editor for DAX without changing any existing behavior. In other words, all of the concepts and examples explained in this book continue to work with Excel 2016.

Sharing Data and Models in Software Engineering

Tim Menzies,Ekrem Kocaguneli,Burak Turhan,Leandro Minku,Fayola Peters
Sharing Data and Models in Software Engineering Book PDF

Author : Tim Menzies,Ekrem Kocaguneli,Burak Turhan,Leandro Minku,Fayola Peters
Publisher : Morgan Kaufmann
Page : 415 pages
File Size : 42,9 Mb
Release : 2014-12-22
Category : Computers
ISBN : 9780124173071

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Sharing Data and Models in Software Engineering by Tim Menzies,Ekrem Kocaguneli,Burak Turhan,Leandro Minku,Fayola Peters Pdf

Data Science for Software Engineering: Sharing Data and Models presents guidance and procedures for reusing data and models between projects to produce results that are useful and relevant. Starting with a background section of practical lessons and warnings for beginner data scientists for software engineering, this edited volume proceeds to identify critical questions of contemporary software engineering related to data and models. Learn how to adapt data from other organizations to local problems, mine privatized data, prune spurious information, simplify complex results, how to update models for new platforms, and more. Chapters share largely applicable experimental results discussed with the blend of practitioner focused domain expertise, with commentary that highlights the methods that are most useful, and applicable to the widest range of projects. Each chapter is written by a prominent expert and offers a state-of-the-art solution to an identified problem facing data scientists in software engineering. Throughout, the editors share best practices collected from their experience training software engineering students and practitioners to master data science, and highlight the methods that are most useful, and applicable to the widest range of projects. Shares the specific experience of leading researchers and techniques developed to handle data problems in the realm of software engineering Explains how to start a project of data science for software engineering as well as how to identify and avoid likely pitfalls Provides a wide range of useful qualitative and quantitative principles ranging from very simple to cutting edge research Addresses current challenges with software engineering data such as lack of local data, access issues due to data privacy, increasing data quality via cleaning of spurious chunks in data

Building Product Models

Charles M Eastman
Building Product Models Book PDF

Author : Charles M Eastman
Publisher : CRC Press
Page : 424 pages
File Size : 47,8 Mb
Release : 1999-07-29
Category : Technology & Engineering
ISBN : 0849302595

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Building Product Models by Charles M Eastman Pdf

Building Product Models thoroughly presents the concepts, technology, and methods now used to work out what will become the building product model - a new, digital representation for architecture, civil engineering, and building construction. Organized into three sections (history, current tools and concepts, and existing efforts and research issues), this resource provides the field of building product modeling with a standard reference as well as a single, comprehensive text for university courses. Until now, all the efforts in building modeling have been reported in research journals and conference proceedings or been made available as draft standards on the Internet. Building Product Models is the only book available on this vital field, bringing together essential aspects of major efforts from the early 1970s to the present.

Models for Multi-State Survival Data

Per Kragh Andersen,Henrik Ravn
Models for Multi State Survival Data Book PDF

Author : Per Kragh Andersen,Henrik Ravn
Publisher : CRC Press
Page : 293 pages
File Size : 43,7 Mb
Release : 2023-10-11
Category : Mathematics
ISBN : 9780429642265

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Models for Multi-State Survival Data by Per Kragh Andersen,Henrik Ravn Pdf

Multi-state models provide a statistical framework for studying longitudinal data on subjects when focus is on the occurrence of events that the subjects may experience over time. They find application particularly in biostatistics, medicine, and public health. The book includes mathematical detail which can be skipped by readers more interested in the practical examples. It is aimed at biostatisticians and at readers with an interest in the topic having a more applied background, such as epidemiology. This book builds on several courses the authors have taught on the subject. Key Features: · Intensity-based and marginal models. · Survival data, competing risks, illness-death models, recurrent events. · Includes a full chapter on pseudo-values. · Intuitive introductions and mathematical details. · Practical examples of event history data. · Exercises. Software code in R and SAS and the data used in the book can be found on the book’s webpage.

Ecological Models and Data in R

Benjamin M. Bolker
Ecological Models and Data in R Book PDF

Author : Benjamin M. Bolker
Publisher : Princeton University Press
Page : 408 pages
File Size : 43,7 Mb
Release : 2008-07-21
Category : Computers
ISBN : 9780691125220

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Ecological Models and Data in R by Benjamin M. Bolker Pdf

Introduction and background; Exploratory data analysis and graphics; Deterministic functions for ecological modeling; Probability and stochastic distributions for ecological modeling; Stochatsic simulation and power analysis; Likelihood and all that; Optimization and all that; Likelihood examples; Standar statistics revisited; Modeling variance; Dynamic models.

Developing Churn Models Using Data Mining Techniques and Social Network Analysis

Klepac, Goran
Developing Churn Models Using Data Mining Techniques and Social Network Analysis Book PDF

Author : Klepac, Goran
Publisher : IGI Global
Page : 326 pages
File Size : 47,7 Mb
Release : 2014-07-31
Category : Computers
ISBN : 9781466662896

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Developing Churn Models Using Data Mining Techniques and Social Network Analysis by Klepac, Goran Pdf

"This book provides an in-depth analysis of attrition modeling relevant to business planning and management, offering insightful and detailed explanation of best practices, tools, and theory surrounding churn prediction and the integration of analytic tools"--Provided by publisher.

Selecting Models from Data

P. Cheeseman,R.W. Oldford
Selecting Models from Data Book PDF

Author : P. Cheeseman,R.W. Oldford
Publisher : Springer Science & Business Media
Page : 475 pages
File Size : 55,8 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9781461226604

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Selecting Models from Data by P. Cheeseman,R.W. Oldford Pdf

This volume is a selection of papers presented at the Fourth International Workshop on Artificial Intelligence and Statistics held in January 1993. These biennial workshops have succeeded in bringing together researchers from Artificial Intelligence and from Statistics to discuss problems of mutual interest. The exchange has broadened research in both fields and has strongly encour aged interdisciplinary work. The theme ofthe 1993 AI and Statistics workshop was: "Selecting Models from Data". The papers in this volume attest to the diversity of approaches to model selection and to the ubiquity of the problem. Both statistics and artificial intelligence have independently developed approaches to model selection and the corresponding algorithms to implement them. But as these papers make clear, there is a high degree of overlap between the different approaches. In particular, there is agreement that the fundamental problem is the avoidence of "overfitting"-Le., where a model fits the given data very closely, but is a poor predictor for new data; in other words, the model has partly fitted the "noise" in the original data.

Practical Deep Learning

Ronald T. Kneusel
Practical Deep Learning Book PDF

Author : Ronald T. Kneusel
Publisher : No Starch Press
Page : 463 pages
File Size : 52,9 Mb
Release : 2021-02-23
Category : Computers
ISBN : 9781718500747

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Practical Deep Learning by Ronald T. Kneusel Pdf

Practical Deep Learning teaches total beginners how to build the datasets and models needed to train neural networks for your own DL projects. If you’ve been curious about machine learning but didn’t know where to start, this is the book you’ve been waiting for. Focusing on the subfield of machine learning known as deep learning, it explains core concepts and gives you the foundation you need to start building your own models. Rather than simply outlining recipes for using existing toolkits, Practical Deep Learning teaches you the why of deep learning and will inspire you to explore further. All you need is basic familiarity with computer programming and high school math—the book will cover the rest. After an introduction to Python, you’ll move through key topics like how to build a good training dataset, work with the scikit-learn and Keras libraries, and evaluate your models’ performance. You’ll also learn: How to use classic machine learning models like k-Nearest Neighbors, Random Forests, and Support Vector Machines How neural networks work and how they’re trained How to use convolutional neural networks How to develop a successful deep learning model from scratch You’ll conduct experiments along the way, building to a final case study that incorporates everything you’ve learned. The perfect introduction to this dynamic, ever-expanding field, Practical Deep Learning will give you the skills and confidence to dive into your own machine learning projects.

Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan

Franzi Korner-Nievergelt,Tobias Roth,Stefanie von Felten,Jérôme Guélat,Bettina Almasi,Pius Korner-Nievergelt
Bayesian Data Analysis in Ecology Using Linear Models with R BUGS and Stan Book PDF

Author : Franzi Korner-Nievergelt,Tobias Roth,Stefanie von Felten,Jérôme Guélat,Bettina Almasi,Pius Korner-Nievergelt
Publisher : Academic Press
Page : 328 pages
File Size : 43,7 Mb
Release : 2015-04-04
Category : Science
ISBN : 9780128016787

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Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan by Franzi Korner-Nievergelt,Tobias Roth,Stefanie von Felten,Jérôme Guélat,Bettina Almasi,Pius Korner-Nievergelt Pdf

Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN examines the Bayesian and frequentist methods of conducting data analyses. The book provides the theoretical background in an easy-to-understand approach, encouraging readers to examine the processes that generated their data. Including discussions of model selection, model checking, and multi-model inference, the book also uses effect plots that allow a natural interpretation of data. Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN introduces Bayesian software, using R for the simple modes, and flexible Bayesian software (BUGS and Stan) for the more complicated ones. Guiding the ready from easy toward more complex (real) data analyses ina step-by-step manner, the book presents problems and solutions—including all R codes—that are most often applicable to other data and questions, making it an invaluable resource for analyzing a variety of data types. Introduces Bayesian data analysis, allowing users to obtain uncertainty measurements easily for any derived parameter of interest Written in a step-by-step approach that allows for eased understanding by non-statisticians Includes a companion website containing R-code to help users conduct Bayesian data analyses on their own data All example data as well as additional functions are provided in the R-package blmeco