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Basic Business Analytics Using R


Basic Business Analytics Using R
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Business Analytics Using R A Practical Approach


Business Analytics Using R A Practical Approach
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Author : Umesh R Hodeghatta
language : en
Publisher: Apress
Release Date : 2016-12-27

Business Analytics Using R A Practical Approach written by Umesh R Hodeghatta and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-27 with Computers categories.


Learn the fundamental aspects of the business statistics, data mining, and machine learning techniques required to understand the huge amount of data generated by your organization. This book explains practical business analytics through examples, covers the steps involved in using it correctly, and shows you the context in which a particular technique does not make sense. Further, Practical Business Analytics using R helps you understand specific issues faced by organizations and how the solutions to these issues can be facilitated by business analytics. This book will discuss and explore the following through examples and case studies: An introduction to R: data management and R functions The architecture, framework, and life cycle of a business analytics project Descriptive analytics using R: descriptive statistics and data cleaning Data mining: classification, association rules, and clustering Predictiveanalytics: simple regression, multiple regression, and logistic regression This book includes case studies on important business analytic techniques, such as classification, association, clustering, and regression. The R language is the statistical tool used to demonstrate the concepts throughout the book. What You Will Learn • Write R programs to handle data • Build analytical models and draw useful inferences from them • Discover the basic concepts of data mining and machine learning • Carry out predictive modeling • Define a business issue as an analytical problem Who This Book Is For Beginners who want to understand and learn the fundamentals of analytics using R. Students, managers, executives, strategy and planning professionals, software professionals, and BI/DW professionals.



Basic Business Analytics Using R


Basic Business Analytics Using R
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Author : Dr. Mahavir M. Shetiya
language : en
Publisher: Thakur Publication Private Limited
Release Date : 2023-11-10

Basic Business Analytics Using R written by Dr. Mahavir M. Shetiya and has been published by Thakur Publication Private Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-10 with Education categories.


Buy BASIC BUSINESS ANALYTICS USING R e-Book for Mba 2nd Semester in English language specially designed for SPPU ( Savitribai Phule Pune University ,Maharashtra) By Thakur publication.



Practical Business Analytics Using R And Python


Practical Business Analytics Using R And Python
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Author : Umesh R. Hodeghatta
language : en
Publisher: Apress
Release Date : 2023-01-27

Practical Business Analytics Using R And Python written by Umesh R. Hodeghatta and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-27 with Computers categories.


This book illustrates how data can be useful in solving business problems. It explores various analytics techniques for using data to discover hidden patterns and relationships, predict future outcomes, optimize efficiency and improve the performance of organizations. You’ll learn how to analyze data by applying concepts of statistics, probability theory, and linear algebra. In this new edition, both R and Python are used to demonstrate these analyses. Practical Business Analytics Using R and Python also features new chapters covering databases, SQL, Neural networks, Text Analytics, and Natural Language Processing. Part one begins with an introduction to analytics, the foundations required to perform data analytics, and explains different analytics terms and concepts such as databases and SQL, basic statistics, probability theory, and data exploration. Part two introduces predictive models using statistical machine learning and discusses concepts like regression, classification, and neural networks. Part three covers two of the most popular unsupervised learning techniques, clustering and association mining, as well as text mining and natural language processing (NLP). The book concludes with an overview of big data analytics, R and Python essentials for analytics including libraries such as pandas and NumPy. Upon completing this book, you will understand how to improve business outcomes by leveraging R and Python for data analytics. What You Will Learn Master the mathematical foundations required for business analytics Understand various analytics models and data mining techniques such as regression, supervised machine learning algorithms for modeling, unsupervised modeling techniques, and how to choose the correct algorithm for analysis in any given task Use R and Python to develop descriptive models, predictive models, and optimize models Interpret and recommend actions based on analytical model outcomes Who This Book Is For Software professionals and developers, managers, and executives who want to understand and learn the fundamentals of analytics using R and Python.



R For Business Analytics


R For Business Analytics
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Author : A Ohri
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-09-14

R For Business Analytics written by A Ohri 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 2012-09-14 with Business & Economics categories.


This book examines common tasks performed by business analysts and helps the reader navigate the wealth of information in R and its 4000 packages to create useful analytics applications. Includes interviews with corporate users of R, and easy-to-use examples.



Business Analytics In Practice


Business Analytics In Practice
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Author : Vinaytosh Mishra
language : en
Publisher:
Release Date : 2023

Business Analytics In Practice written by Vinaytosh Mishra and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with Business categories.


Business Analytics is a field that aims to solve business problems using methods such as statistical analysis, operations research, machine learning, and artificial intelligence. In general, the data associated with real-life problems are not clearly defined, multidimensional, and complex. The situation requires sophisticated tools to help decision-makers. R is one of the most widely used programming languages having a distinct advantage in statistical analysis and data visualization. It is an easy-to-use language with an interactive user interface available. Moreover, it has an open-source and continuously evolving programming environment. This guide is divided into three major sections namely (1) Fundamentals of R Software (2) Installing R-Package (3) Running Basic R Functions, and (4) Solving a business problem using R. The guide is written in simple jargon-free language and provides easy-follow steps to install and use R. The goal of this guide is to introduce R to beginners and sensitize them to the potential of R. The difficulty level of this guide is somewhere near the advanced undergraduate level. Reference for additional web resources books is given at the end of the guide for further readings.



Machine Learning For Business Analytics


Machine Learning For Business Analytics
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Author : Galit Shmueli
language : en
Publisher: John Wiley & Sons
Release Date : 2023-03-22

Machine Learning For Business Analytics written by Galit Shmueli 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 2023-03-22 with Computers categories.


MACHINE LEARNING FOR BUSINESS ANALYTICS Machine learning —also known as data mining or data analytics— is a fundamental part of data science. It is used by organizations in a wide variety of arenas to turn raw data into actionable information. Machine Learning for Business Analytics: Concepts, Techniques, and Applications in R provides a comprehensive introduction and an overview of this methodology. This best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation, and network analytics. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques. This is the second R edition of Machine Learning for Business Analytics. This edition also includes: A new co-author, Peter Gedeck, who brings over 20 years of experience in machine learning using R An expanded chapter focused on discussion of deep learning techniques A new chapter on experimental feedback techniques including A/B testing, uplift modeling, and reinforcement learning A new chapter on responsible data science Updates and new material based on feedback from instructors teaching MBA, Masters in Business Analytics and related programs, undergraduate, diploma and executive courses, and from their students A full chapter devoted to relevant case studies with more than a dozen cases demonstrating applications for the machine learning techniques End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, slides, and case solutions This textbook is an ideal resource for upper-level undergraduate and graduate level courses in data science, predictive analytics, and business analytics. It is also an excellent reference for analysts, researchers, and data science practitioners working with quantitative data in management, finance, marketing, operations management, information systems, computer science, and information technology.



Introduction To R For Business Intelligence


Introduction To R For Business Intelligence
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Author : Jay Gendron
language : en
Publisher:
Release Date : 2016

Introduction To R For Business Intelligence written by Jay Gendron and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Business planning categories.


Learn how to leverage the power of R for Business Intelligence About This Book Use this easy-to-follow guide to leverage the power of R analytics and make your business data more insightful. This highly practical guide teaches you how to develop dashboards that help you make informed decisions using R. Learn the A to Z of working with data for Business Intelligence with the help of this comprehensive guide. Who This Book Is For This book is for data analysts, business analysts, data science professionals or anyone who wants to learn analytic approaches to business problems. Basic familiarity with R is expected. What You Will Learn Extract, clean, and transform data Validate the quality of the data and variables in datasets Learn exploratory data analysis Build regression models Implement popular data-mining algorithms Visualize results using popular graphs Publish the results as a dashboard through Interactive Web Application frameworks In Detail Explore the world of Business Intelligence through the eyes of an analyst working in a successful and growing company. Learn R through use cases supporting different functions within that company. This book provides data-driven and analytically focused approaches to help you answer questions in operations, marketing, and finance. In Part 1, you will learn about extracting data from different sources, cleaning that data, and exploring its structure. In Part 2, you will explore predictive models and cluster analysis for Business Intelligence and analyze financial times series. Finally, in Part 3, you will learn to communicate results with sharp visualizations and interactive, web-based dashboards. After completing the use cases, you will be able to work with business data in the R programming environment and realize how data science helps make informed decisions and develops business strategy. Along the way, you will find helpful tips about R and Business Intelligence. Style and approach This book will take a step-by-step approach and instruct you in how you can achieve Business Intelligence from scratch using R. We will start with extracting data and then move towards exploring, analyzing, and visualizing it. Eventually, you will learn how to create insightful dashboards that help you make informed decisions - and all of this with the help of real-life examples.



Business Analytics With R


Business Analytics With R
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Author : Kumar P
language : en
Publisher: Independently Published
Release Date : 2024-11-15

Business Analytics With R written by Kumar P and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-15 with Business & Economics categories.


In today's fast-paced and data-driven world, businesses are increasingly relying on data to guide their strategies, optimize operations, and stay ahead of the competition. From customer behavior to market trends, every facet of a business generates vast amounts of data-data that holds the key to better decision-making, enhanced performance, and greater profitability. However, unlocking the potential of this data requires more than just access to it; it requires the tools, techniques, and frameworks that allow us to analyze, interpret, and act on the insights it provides. This book, Business Analytics with R: Unlocking Data-Driven Insights for Business Solutions, is designed to provide you with the knowledge and practical skills necessary to leverage the power of data in business contexts. Whether you are a business analyst, data scientist, or business manager, this book aims to equip you with a solid foundation in business analytics using R, one of the most powerful and widely used open-source programming languages for statistical analysis and data science. R has become an indispensable tool in the world of analytics. Its flexibility, vast library of packages, and user-friendly environment make it ideal for analyzing and visualizing data, building predictive models, and uncovering trends that drive business success. In this book, we will guide you through the fundamentals of R, as well as advanced techniques in business analytics, with a focus on solving real-world business problems. In addition to the theoretical underpinnings of business analytics, the book is packed with hands-on examples, practical exercises, and case studies that demonstrate how these concepts are applied in real-world business scenarios. Whether you are trying to optimize marketing campaigns, improve sales forecasts, or understand customer behavior, the tools and techniques you will learn in this book will help you derive actionable insights from your data. Who Should Read This Book? This book is aimed at anyone interested in applying business analytics to solve real-world problems using R. It is ideal for: Business Analysts: Who want to enhance their analytical skills and learn how to use R for solving business problems. Data Scientists: Who are looking to expand their knowledge in business contexts and understand how to apply advanced analytics in a business environment. Managers and Decision Makers: Who want to understand how data-driven insights can inform strategic business decisions. Students: Who are learning business analytics, data science, or related fields and want a practical guide to applying analytics using R This book is structured to cater to both beginners and more advanced users. Each chapter begins with a conceptual introduction to the topic, followed by practical, hands-on examples using R. You will find step-by-step instructions, along with clear explanations of the code and the business implications of the results. Whether you are working through the chapters in order or focusing on specific topics, you will gain the skills necessary to apply business analytics in your organization. So, let's dive in and begin unlocking the true potential of your business data with R!



Predictive Analytics For Business Using R


Predictive Analytics For Business Using R
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Author : Russell R Barton
language : en
Publisher: World Scientific
Release Date : 2024-07-16

Predictive Analytics For Business Using R written by Russell R Barton and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-16 with Business & Economics categories.


The fields of mathematical statistics, statistical graphics, computer science and operations research have created the rich set of methods now called Analytics. Often analytics is characterized along three poles: descriptive analytics (what do data tell us), predictive analytics (what can be forecast based on the data, and with what certainty), and prescriptive analytics (how can the data inform changes to improve system performance).This book focuses on the second pole, predictive analytics. The areas of predicting a number, a class, and dynamic behavior are distinct, with different methods. This text has three parts based on these areas. Topics in predicting a number include simple and multiple linear regression, transformation of variables, analysis of observational data via cross-validation, the generalized linear model, designed experiments, and Gaussian process and neural network regression. Classification methods include neural networks, logistic regression, k-nearest neighbor, and linear discriminant analysis. Methods for predicting dynamic behavior include trend analysis, time series analysis and discrete-event dynamic simulation.Characterizing prediction uncertainty is a key focus of this text. The text provides analytic methods appropriate to each area, with an explicit process for applying such methods. Case data with corresponding R code are used to illustrate each method.Predictive Analytics for Business using R is designed for a hybrid class structure. Class sessions can be a blend of lecture format and flipped classroom case analyses. In a two-meetings-per-week fifteen-week structure, one day per week would be devoted to explaining methodology and presenting a case study, with the second day focused on coaching. Given the case structure, the text does not contain homework problems. Instead, at the end of each chapter there are links to cases posted online.



General Catalog University Of California Santa Cruz


General Catalog University Of California Santa Cruz
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Author : University of California, Santa Cruz
language : en
Publisher:
Release Date : 2008

General Catalog University Of California Santa Cruz written by University of California, Santa Cruz and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.