Data Distribution
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Statistics
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Author : David C. LeBlanc
language : en
Publisher: Jones & Bartlett Learning
Release Date : 2004
Statistics written by David C. LeBlanc and has been published by Jones & Bartlett Learning this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Mathematics categories.
Designed for students majoring in the life, health, and natural sciences, Statistics: Concepts and Applications for Science is a text and workbook package that introduces statistics with an important emphasis on the real-world applications of statistical reasoning and procedures. Through intensive exposure to the core concepts of statistics in the context of science, students acquire the skills and understanding they need to formulate valid research designs, implement statistical analysis, interpret data, and explain their results.
Data Driven Business Decisions
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Author : Chris J. Lloyd
language : en
Publisher: John Wiley & Sons
Release Date : 2011-10-25
Data Driven Business Decisions written by Chris J. Lloyd and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-10-25 with Business & Economics categories.
A hands-on guide to the use of quantitative methods and software for making successful business decisions The appropriate use of quantitative methods lies at the core of successful decisions made by managers, researchers, and students in the field of business. Providing a framework for the development of sound judgment and the ability to utilize quantitative and qualitative approaches, Data Driven Business Decisions introduces readers to the important role that data plays in understanding business outcomes, addressing four general areas that managers need to know about: data handling and Microsoft Excel, uncertainty, the relationship between inputs and outputs, and complex decisions with trade-offs and uncertainty. Grounded in the author's own classroom approach to business statistics, the book reveals how to use data to understand the drivers of business outcomes, which in turn allows for data-driven business decisions. A basic, non-mathematical foundation in statistics is provided, outlining for readers the tools needed to link data with business decisions; account for uncertainty in the actions of others and in patterns revealed by data; handle data in Excel; translate their analysis into simple business terms; and present results in simple tables and charts. The author discusses key data analytic frameworks, such as decision trees and multiple regression, and also explores additional topics, including: Use of the Excel® functions Solver and Goal Seek Partial correlation and auto-correlation Interactions and proportional variation in regression models Seasonal adjustment and what it reveals Basic portfolio theory as an introduction to correlations Chapters are introduced with case studies that integrate simple ideas into the larger business context, and are followed by further details, raw data, and motivating insights. Algebraic notation is used only when necessary, and throughout the book, the author utilizes real-world examples from diverse areas such as market surveys, finance, economics, and business ethics. Excel® add-ins StatproGo and TreePlan are showcased to demonstrate execution of the techniques, and a related website features extensive programming instructions as well as insights, data sets, and solutions to problems included in the material. Data Driven Business Decisions is an excellent book for MBA quantitative analysis courses or undergraduate general statistics courses. It also serves as a valuable reference for practicing MBAs and practitioners in the fields of statistics, business, and finance.
Data Representations Transformations And Statistics For Visual Reasoning
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Author : Ross Maciejewski
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2011
Data Representations Transformations And Statistics For Visual Reasoning written by Ross Maciejewski and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Business & Economics categories.
Analytical reasoning techniques are methods by which users explore their data to obtain insight and knowledge that can directly support situational awareness and decision making. Recently, the analytical reasoning process has been augmented through the use of interactive visual representations and tools which utilize cognitive, design and perceptual principles. These tools are commonly referred to as visual analytics tools, and the underlying methods and principles have roots in a variety of disciplines. This chapter provides an introduction to young researchers as an overview of common visual representations and statistical analysis methods utilized in a variety of visual analytics systems. The application and design of visualization and analytical algorithms are subject to design decisions, parameter choices, and many conflicting requirements. As such, this chapter attempts to provide an initial set of guidelines for the creation of the visual representation, including pitfalls and areas where the graphics can be enhanced through interactive exploration. Basic analytical methods are explored as a means of enhancing the visual analysis process, moving from visual analysis to visual analytics. Table of Contents: Data Types / Color Schemes / Data Preconditioning / Visual Representations and Analysis / Summary
Introduction To Data Governance For Machine Learning Systems
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Author : Aditya Nandan Prasad
language : en
Publisher: Springer Nature
Release Date : 2024-12-13
Introduction To Data Governance For Machine Learning Systems written by Aditya Nandan Prasad and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-13 with Mathematics categories.
This book is the first comprehensive guide to the intersection of data governance and machine learning (ML) projects. As ML applications proliferate, the quality, reliability, and ethical use of data is central to their success, which gives ML data governance unprecedented significance. However, adapting data governance principles to ML systems presents unique, complex challenges. Author Aditya Nandan Prasad equips you with the knowledge and tools needed to navigate this dynamic landscape effectively. Through this guide, you will learn to implement robust and responsible data governance practices, ensuring the development of sustainable, ethical, and future-proofed AI applications. The book begins by covering fundamental principles and practices of underlying ML applications and data governance before diving into the unique challenges and opportunities at play when adapting data governance theory and practice to ML projects, including establishing governance frameworks, ensuring data quality and interpretability, preprocessing, and the ethical implications of ML algorithms and techniques, from mitigating bias in AI systems to the importance of transparency in models. Monitoring and maintaining ML systems performance is also covered in detail, along with regulatory compliance and risk management considerations. Moreover, the book explores strategies for fostering a data-driven culture within organizations and offers guidance on change management to ensure successful adoption of data governance initiatives. Looking ahead, the book examines future trends and emerging challenges in ML data governance, such as Explainable AI (XAI) and the increasing complexity of data. What You Will Learn Comprehensive understanding of machine learning and data governance, including fundamental principles, critical practices, and emerging challenges Navigating the complexities of managing data effectively within the context of machine learning projects Practical strategies and best practices for implementing effective data governance in machine learning projects Key aspects such as data quality, privacy, security, and ethical considerations, ensuring responsible and effective use of data Preparation for the evolving landscape of ML data governance with a focus on future trends and emerging challenges in the rapidly evolving field of AI and machine learning Who This Book Is For Data professionals, including data scientists, data engineers, AI developers, or data governance specialists, as well as managers or decision makers looking to implement or improve data governance practices for machine learning projects
Languages And Compilers For Parallel Computing
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Author : Bill Pugh
language : en
Publisher: Springer Science & Business Media
Release Date : 2005-12-13
Languages And Compilers For Parallel Computing written by Bill Pugh and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-12-13 with Computers categories.
This book constitutes the thoroughly refereed post-proceedings of the 15th International Workshop on Languages and Compilers for Parallel Processing, LCPC 2002, held in College Park, MD, USA in July 2002. The 26 revised full papers presented were carefully selected during two rounds of reviewing and improvement from 32 submissions. All current issues in parallel processing are addressed, in particular memory-constrained computation, compiler optimization, performance studies, high-level languages, programming language consistency models, dynamic parallelization, parallelization of data mining algorithms, parallelizing compilers, garbage collection algorithms, and evaluation of iterative compilation.
Tribo Informatics
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Author : Zhinan Zhang
language : en
Publisher: CRC Press
Release Date : 2024-04-11
Tribo Informatics written by Zhinan Zhang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-11 with Technology & Engineering categories.
This book details how artificial intelligence and other informatic methods can be applied to the field of tribology. Using problems often found within tribological condition monitoring, behaviour prediction, system optimization and mechanism analysis, the book covers methods used such as Artificial Neural Networks (ANN). Including case studies throughout, the book offers an accessible introduction to tribological research, beginning with background on the theory behind tribo-informatics, and updates in the latest technology. It describes how to establish a tribo-informatics database, methods through which to express tribo-systems such as Artificial Neural Networks (ANN), Support Vector Machines (SVM), K-Nearest Neighbor (KNN), and Random Forest (RF), and its applications. It can be used in state monitoring, behaviour prediction and system optimization. Through case studies, practical examples of how tribo-informatics can be implemented are shown throughout various industries. This book will be of interest to students and researchers in the field of tribology, friction, wear and artificial intelligence.
The Data Warehouse Challenge
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Author : Michael H. Brackett
language : en
Publisher:
Release Date : 1996-07-27
The Data Warehouse Challenge written by Michael H. Brackett and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-07-27 with Computers categories.
Information Technology/Database Management "...the definitive source for understanding modern data architecture. Other books have bits and pieces of architecture described, but nowhere else is there a single source that has all the components of modern data architecture in one place in an organized and readable manner." -From the Foreword by William H. Inmon The technology for compiling data has evolved to the point where most organizations now amass information faster than they can use it. The bad news is that most of that data is disparate, scattered across different databases and platforms. The time has come to tame the data chaos, and this invaluable resource shows you how. Michael H. Brackett schools you in a variety of techniques for creating a cohesive data structure that everyone in your organization can use. Step-by-step, he guides you through the entire process of planning, building, and programming a data warehouse tailored to your organization's needs. You learn how to: * Prepare and evaluate existing data for a data warehouse * Cross reference data so it's easy to find in all corporate locations * Prepare data for client/server systems * Improve the consistency and quality of existing and future data * Manage a data warehouse The Data Warehouse Challenge is an indispensable tool for database administrators and developers, systems programmers and analysts, and all those involved with helping their organizations rise to the challenge of taming data chaos.
Cascon
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Author :
language : en
Publisher:
Release Date : 1996
Cascon written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Computer software categories.
Estimation Of Quantiles In A Simulation Model Based On Artificial Neural Networks
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Author : Sevda Alaca
language : en
Publisher: GRIN Verlag
Release Date : 2017-07-10
Estimation Of Quantiles In A Simulation Model Based On Artificial Neural Networks written by Sevda Alaca and has been published by GRIN Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-10 with Mathematics categories.
Master's Thesis from the year 2017 in the subject Mathematics - Stochastics, grade: 1,3, Technical University of Darmstadt, language: English, abstract: This thesis deals with the development of an "alpha"-quantile estimate based on a surrogate model with the use of artificial neural networks. Using artificial neural networks as an estimate is considered a nonparametric approach. The estimation of a specific quantile of a data population is a widely used statistical task and a comprehensive way to discover the true relationship among variables. It can be classified as nonparametric regression, where it is one of the standard tasks. The most common selected levels for estimation are the first, second and third quartile (25, 50 and 75 percent). The quantile level is given by "alpha". A 25 percent quantile for example has 25 percent of the data distribution below the named quantile and 75 percent of the data distribution above it. Sometimes the tail regions of a population characteristic are of interest rather than the core of the distribution. Quantile estimation is applied in many different contexts - financial economics, survival analysis and environmental modelling are only a few of them.
International Record Of Medicine And General Practice Clinics
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Author : Frank Pierce Foster
language : en
Publisher:
Release Date : 1885
International Record Of Medicine And General Practice Clinics written by Frank Pierce Foster and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1885 with Medicine categories.