Essentials Of Modeling And Analytics

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Essentials Of Modeling And Analytics

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Author : David B. Speights
language : en
Publisher: Routledge
Release Date : 2017-09-11

Essentials Of Modeling And Analytics written by David B. Speights and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-11 with Political Science categories.

Essentials of Modeling and Analytics illustrates how and why analytics can be used effectively by loss prevention staff. The book offers an in-depth overview of analytics, first illustrating how analytics are used to solve business problems, then exploring the tools and training that staff will need in order to engage solutions. The text also covers big data analytical tools and discusses if and when they are right for retail loss prevention professionals, and illustrates how to use analytics to test the effectiveness of loss prevention initiatives. Ideal for loss prevention personnel on all levels, this book can also be used for loss prevention analytics courses. Essentials of Modeling and Analytics was named one of the best Analytics books of all time by BookAuthority, one of the world's leading independent sites for nonfiction book recommendations.

Data Modeling Essentials

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Author : Graeme Simsion
language : en
Publisher: Elsevier
Release Date : 2004-12-03

Data Modeling Essentials written by Graeme Simsion and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-12-03 with Computers categories.

Data Modeling Essentials, Third Edition, covers the basics of data modeling while focusing on developing a facility in techniques, rather than a simple familiarization with "the rules". In order to enable students to apply the basics of data modeling to real models, the book addresses the realities of developing systems in real-world situations by assessing the merits of a variety of possible solutions as well as using language and diagramming methods that represent industry practice. This revised edition has been given significantly expanded coverage and reorganized for greater reader comprehension even as it retains its distinctive hallmarks of readability and usefulness. Beginning with the basics, the book provides a thorough grounding in theory before guiding the reader through the various stages of applied data modeling and database design. Later chapters address advanced subjects, including business rules, data warehousing, enterprise-wide modeling and data management. It includes an entirely new section discussing the development of logical and physical modeling, along with new material describing a powerful technique for model verification. It also provides an excellent resource for additional lectures and exercises. This text is the ideal reference for data modelers, data architects, database designers, DBAs, and systems analysts, as well as undergraduate and graduate-level students looking for a real-world perspective. - Thorough coverage of the fundamentals and relevant theory - Recognition and support for the creative side of the process - Expanded coverage of applied data modeling includes new chapters on logical and physical database design - New material describing a powerful technique for model verification - Unique coverage of the practical and human aspects of modeling, such as working with business specialists, managing change, and resolving conflict

Ibm Spss Modeler Essentials

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Author : Jose Jesus Salcedo
language : en
Publisher:
Release Date : 2017-12-21

Ibm Spss Modeler Essentials written by Jose Jesus Salcedo and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-21 with Data mining categories.

Get to grips with the fundamentals of data mining and predictive analytics with IBM SPSS Modeler Key Features Get up-and-running with IBM SPSS Modeler without going into too much depth. Identify interesting relationships within your data and build effective data mining and predictive analytics solutions A quick, easy-to-follow guide to give you a fundamental understanding of SPSS Modeler, written by the best in the business Book Description IBM SPSS Modeler allows users to quickly and efficiently use predictive analytics and gain insights from your data. With almost 25 years of history, Modeler is the most established and comprehensive Data Mining workbench available. Since it is popular in corporate settings, widely available in university settings, and highly compatible with all the latest technologies, it is the perfect way to start your Data Science and Machine Learning journey. This book takes a detailed, step-by-step approach to introducing data mining using the de facto standard process, CRISP-DM, and Modeler's easy to learn "visual programming" style. You will learn how to read data into Modeler, assess data quality, prepare your data for modeling, find interesting patterns and relationships within your data, and export your predictions. Using a single case study throughout, this intentionally short and focused book sticks to the essentials. The authors have drawn upon their decades of teaching thousands of new users, to choose those aspects of Modeler that you should learn first, so that you get off to a good start using proven best practices. This book provides an overview of various popular data modeling techniques and presents a detailed case study of how to use CHAID, a decision tree model. Assessing a model's performance is as important as building it; this book will also show you how to do that. Finally, you will see how you can score new data and export your predictions. By the end of this book, you will have a firm understanding of the basics of data mining and how to effectively use Modeler to build predictive models. What you will learn Understand the basics of data mining and familiarize yourself with Modeler's visual programming interface Import data into Modeler and learn how to properly declare metadata Obtain summary statistics and audit the quality of your data Prepare data for modeling by selecting and sorting cases, identifying and removing duplicates, combining data files, and modifying and creating fields Assess simple relationships using various statistical and graphing techniques Get an overview of the different types of models available in Modeler Build a decision tree model and assess its results Score new data and export predictions Who this book is for This book is ideal for those who are new to SPSS Modeler and want to start using it as quickly as possible, without going into too much detail. An understanding of basic data mining concepts will be helpful, to get the best out of the book.

Correlated Data Analysis Modeling Analytics And Applications

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Author : Xue-Kun Song
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-07-27

Correlated Data Analysis Modeling Analytics And Applications written by Xue-Kun Song 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 2007-07-27 with Mathematics categories.

This book covers recent developments in correlated data analysis. It utilizes the class of dispersion models as marginal components in the formulation of joint models for correlated data. This enables the book to cover a broader range of data types than the traditional generalized linear models. The reader is provided with a systematic treatment for the topic of estimating functions, and both generalized estimating equations (GEE) and quadratic inference functions (QIF) are studied as special cases. In addition to the discussions on marginal models and mixed-effects models, this book covers new topics on joint regression analysis based on Gaussian copulas.

R For Data Science

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Author : Hadley Wickham
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2016-12-12

R For Data Science written by Hadley Wickham and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-12 with Computers categories.

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

Essentials Of Time Series For Financial Applications

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Author : Massimo Guidolin
language : en
Publisher: Academic Press
Release Date : 2018-05-29

Essentials Of Time Series For Financial Applications written by Massimo Guidolin and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-29 with Business & Economics categories.

Essentials of Time Series for Financial Applications serves as an agile reference for upper level students and practitioners who desire a formal, easy-to-follow introduction to the most important time series methods applied in financial applications (pricing, asset management, quant strategies, and risk management). Real-life data and examples developed with EViews illustrate the links between the formal apparatus and the applications. The examples either directly exploit the tools that EViews makes available or use programs that by employing EViews implement specific topics or techniques. The book balances a formal framework with as few proofs as possible against many examples that support its central ideas. Boxes are used throughout to remind readers of technical aspects and definitions and to present examples in a compact fashion, with full details (workout files) available in an on-line appendix. The more advanced chapters provide discussion sections that refer to more advanced textbooks or detailed proofs. - Provides practical, hands-on examples in time-series econometrics - Presents a more application-oriented, less technical book on financial econometrics - Offers rigorous coverage, including technical aspects and references for the proofs, despite being an introduction - Features examples worked out in EViews (9 or higher)

The Basics Of Financial Modeling

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Author : Jack Avon
language : en
Publisher: Apress
Release Date : 2014-11-21

The Basics Of Financial Modeling written by Jack Avon and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-21 with Business & Economics categories.

Learn to create and understand financial models that assess the value of your company, the projects it undertakes, and its future earnings/profit projections. Follow this step-by-step guide organized in a quick-read format to build an accurate and effective financial model from the ground up. In this short book, The Basics of Financial Modeling—an abridgment of the Handbook of Financial Modeling—author Jack Avon equips business professionals who are familiar with financial statements and accounting reports to become truly proficient. Based on the author's extensive experience building models in business and finance, and teaching others to do the same, this book takes you through the financial modeling process, starting with a general overview of the history and evolution of financial modeling. It then moves on to more technical topics, such as the principles of financial modeling and the proper way to approach a financial modeling assignment, beforecovering key application areas for modeling in Microsoft Excel. What You'll Learn Understand the accounting and finance concepts that underpin working financial models Approach financial issues and solutions from a modeler's perspective Think about end users when developing a financial model Plan, design, and build a financial model Who This Book Is For Beginning to intermediate modelers who wish to expand and enhance their knowledge of using Excel to build and analyze financial models

Statistics 101

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Author : David Borman
language : en
Publisher: Simon and Schuster
Release Date : 2018-12-18

Statistics 101 written by David Borman 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 2018-12-18 with Mathematics categories.

A comprehensive guide to statistics—with information on collecting, measuring, analyzing, and presenting statistical data—continuing the popular 101 series. Data is everywhere. In the age of the internet and social media, we’re responsible for consuming, evaluating, and analyzing data on a daily basis. From understanding the percentage probability that it will rain later today, to evaluating your risk of a health problem, or the fluctuations in the stock market, statistics impact our lives in a variety of ways, and are vital to a variety of careers and fields of practice. Unfortunately, most statistics text books just make us want to take a snooze, but with Statistics 101, you’ll learn the basics of statistics in a way that is both easy-to-understand and apply. From learning the theory of probability and different kinds of distribution concepts, to identifying data patterns and graphing and presenting precise findings, this essential guide can help turn statistical math from scary and complicated, to easy and fun. Whether you are a student looking to supplement your learning, a worker hoping to better understand how statistics works for your job, or a lifelong learner looking to improve your grasp of the world, Statistics 101 has you covered.

Fundamentals Of Machine Learning For Predictive Data Analytics Second Edition

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Author : John D. Kelleher
language : en
Publisher: MIT Press
Release Date : 2020-10-20

Fundamentals Of Machine Learning For Predictive Data Analytics Second Edition written by John D. Kelleher and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-20 with Computers categories.

The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice. Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. This second edition covers recent developments in machine learning, especially in a new chapter on deep learning, and two new chapters that go beyond predictive analytics to cover unsupervised learning and reinforcement learning.

Essentials Of Data Analysis

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Author : Agasti Khatri
language : en
Publisher: Educohack Press
Release Date : 2025-02-20

Essentials Of Data Analysis written by Agasti Khatri and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Computers categories.

"Essentials of Data Analysis" is an indispensable guide that navigates readers through the world of data-driven decision-making. This book presents essential concepts, techniques, and tools in an accessible and user-friendly manner. It serves as a trusted companion for both beginners and professionals in their data analysis journey. We start by laying a solid foundation in data analysis principles, providing a comprehensive understanding of key concepts and methodologies. The book delves into practical techniques for data manipulation, visualization, and exploration, equipping readers with the skills to extract actionable insights from raw data. Real-world examples, case studies, and hands-on exercises bring abstract concepts to life. We emphasize the ethical and responsible use of data, guiding readers through ethical considerations, privacy concerns, and regulatory requirements. This fosters a culture of ethical awareness and accountability. Additionally, we explore emerging trends and technologies shaping the future of data analysis, such as artificial intelligence, machine learning, augmented analytics, and edge computing. By adopting innovative techniques, readers can drive meaningful change within their organizations. "Essentials of Data Analysis" is a valuable resource for enhancing analytical skills, advancing careers, and understanding the role of data in decision-making.