Insights From Data With R
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Insights From Data With R
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Author : Owen L. Petchey
language : en
Publisher:
Release Date : 2021
Insights From Data With R written by Owen L. Petchey and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Electronic books categories.
This accessible and engaging book provides readers with the knowledge, experience, and confidence to work with raw data and unlock essential information (insights) from data summaries and visualisations.
R Programming For Data Analysis
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Author : Peter Simon
language : en
Publisher: Peter Simon
Release Date :
R Programming For Data Analysis written by Peter Simon and has been published by Peter Simon this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Unlock the Power of Data with R Programming for Data Analysis — Your Complete Guide from Beginner to Expert! Are you eager to master data analytics using R programming but unsure where to start? Whether you're a student, aspiring data analyst, or professional looking to upskill, this book is the perfect starting point to learn R for data analysis and become proficient with one of the most powerful tools in the industry. What Makes This Book Your Ultimate Resource for Data Analysis Using R Software? This comprehensive guide covers everything you need to confidently use R software data analysis tools, starting from installation to mastering essential programming concepts. You’ll learn how to harness the full potential of the R language for data science and data analytics with R programming to unlock actionable insights from your data. Inside You’ll Discover: Step-by-step guidance on setting up R and RStudio, the leading R data analysis software, so you can get started quickly. Master core data structures in R language data analysis: vectors, lists, data frames, and factors—building blocks for efficient data analysis using R programming. Practical techniques for cleaning, transforming, and visualizing data—skills every R data analyst needs. How to apply data science with R basics to perform statistical analysis and modeling. Real-world examples that make learning intuitive and effective—like a top R programming course or R programming training session. Who Should Read This? Beginners wanting to learn R programming specifically for data science with R Analysts seeking to upgrade their skills using the best r analysis software Students enrolled in a data science with R course or anyone learning the r programming language course Professionals eager to master r coding language for actionable data analytics R programming Why Choose This Book Over Others? This isn’t just another technical manual. It’s designed to simplify the complexities of R programming for data analysis with clear explanations, practical exercises, and a focus on real-world applications. Whether you want to become a skilled R language for data analytics professional or simply want to understand your data better, this book makes it achievable. Start your journey to becoming a confident data analyst today. Scroll up and order R Programming for Data Analysis now—unlock insights, drive decisions, and transform data into success!
R For Data Analysis In Easy Steps 2nd Edition
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Author : Mike McGrath
language : en
Publisher: In Easy Steps Limited
Release Date : 2023-06-05
R For Data Analysis In Easy Steps 2nd Edition written by Mike McGrath and has been published by In Easy Steps Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-05 with Computers categories.
The R language is widely used by statisticians for data analysis, and the popularity of R programming has therefore increased substantially in recent years. The emerging Internet of Things (IoT) gathers increasing amounts of data that can be analyzed to gain useful insights into trends. R for Data Analysis in easy steps, 2nd edition has an easy-to-follow style that will appeal to anyone who wants to produce graphic visualizations to gain insights from gathered data. The book begins by explaining core programming principles of the R programming language, which stores data in “vectors” from which simple graphs can be plotted. Next, it describes how to create “matrices” to store and manipulate data from which graphs can be plotted to provide better insights. This book then demonstrates how to create “data frames” from imported data sets, and how to employ the “Grammar of Graphics” to produce advanced visualizations that can best illustrate useful insights from your data. R for Data Analysis in easy steps, 2nd edition contains separate chapters on the major features of the R programming language. There are complete example programs that demonstrate how to create Line graphs, Bar charts, Histograms, Scatter graphs, Box plots, and more. The code for each R script is listed, together with screenshots that illustrate the actual output when that script has been executed. The free, downloadable example R code is provided for clearer understanding. By the end of this book you will have gained a sound understanding of R programming, and be able to write your own scripts that can be executed to produce graphic visualizations for data analysis. You need have no previous knowledge of any programming language, so it's ideal for the newcomer to computer programming. Updated for the latest version of R. Contents: Getting started Storing values Performing operations Testing conditions Employing functions Building matrices Constructing data frames Producing quick plots Telling stories with data Plotting perfection
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.
Applied Analytics Through Case Studies Using Sas And R
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Author : Deepti Gupta
language : en
Publisher: Apress
Release Date : 2018-08-03
Applied Analytics Through Case Studies Using Sas And R written by Deepti Gupta and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-03 with Computers categories.
Examine business problems and use a practical analytical approach to solve them by implementing predictive models and machine learning techniques using SAS and the R analytical language. This book is ideal for those who are well-versed in writing code and have a basic understanding of statistics, but have limited experience in implementing predictive models and machine learning techniques for analyzing real world data. The most challenging part of solving industrial business problems is the practical and hands-on knowledge of building and deploying advanced predictive models and machine learning algorithms. Applied Analytics through Case Studies Using SAS and R is your answer to solving these business problems by sharpening your analytical skills. What You'll Learn Understand analytics and basic data concepts Use an analytical approach to solve Industrial business problems Build predictive model with machine learning techniques Create and apply analytical strategies Who This Book Is For Data scientists, developers, statisticians, engineers, and research students with a great theoretical understanding of data and statistics who would like to enhance their skills by getting practical exposure in data modeling.
Business Analytics With R And Python
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Author : David L. Olson
language : en
Publisher: Springer Nature
Release Date : 2024-07-30
Business Analytics With R And Python written by David L. Olson and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-30 with Computers categories.
This book provides an overview of data mining methods in the field of business. Business management faces challenges in serving customers in better ways, in identifying risks, and analyzing the impact of decisions. Of the three types of analytic tools, descriptive analytics focuses on what has happened and predictive analytics extends statistical and/or artificial intelligence to provide forecasting capability. Chapter 1 provides an overview of business management problems. Chapter 2 describes how analytics and knowledge management have been used to better cope with these problems. Chapter 3 describes initial data visualization tools. Chapter 4 describes association rules and software support. Chapter 5 describes cluster analysis with software demonstration. Chapter 6 discusses time series analysis with software demonstration. Chapter 7 describes predictive classification data mining tools. Applications of the context of management are presented in Chapter 8. Chapter 9 covers prescriptive modeling in business and applications of artificial intelligence.
Big Data Analytics With R
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Author : Simon Walkowiak
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-07-29
Big Data Analytics With R written by Simon Walkowiak and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-29 with Computers categories.
Utilize R to uncover hidden patterns in your Big Data About This Book Perform computational analyses on Big Data to generate meaningful results Get a practical knowledge of R programming language while working on Big Data platforms like Hadoop, Spark, H2O and SQL/NoSQL databases, Explore fast, streaming, and scalable data analysis with the most cutting-edge technologies in the market Who This Book Is For This book is intended for Data Analysts, Scientists, Data Engineers, Statisticians, Researchers, who want to integrate R with their current or future Big Data workflows. It is assumed that readers have some experience in data analysis and understanding of data management and algorithmic processing of large quantities of data, however they may lack specific skills related to R. What You Will Learn Learn about current state of Big Data processing using R programming language and its powerful statistical capabilities Deploy Big Data analytics platforms with selected Big Data tools supported by R in a cost-effective and time-saving manner Apply the R language to real-world Big Data problems on a multi-node Hadoop cluster, e.g. electricity consumption across various socio-demographic indicators and bike share scheme usage Explore the compatibility of R with Hadoop, Spark, SQL and NoSQL databases, and H2O platform In Detail Big Data analytics is the process of examining large and complex data sets that often exceed the computational capabilities. R is a leading programming language of data science, consisting of powerful functions to tackle all problems related to Big Data processing. The book will begin with a brief introduction to the Big Data world and its current industry standards. With introduction to the R language and presenting its development, structure, applications in real world, and its shortcomings. Book will progress towards revision of major R functions for data management and transformations. Readers will be introduce to Cloud based Big Data solutions (e.g. Amazon EC2 instances and Amazon RDS, Microsoft Azure and its HDInsight clusters) and also provide guidance on R connectivity with relational and non-relational databases such as MongoDB and HBase etc. It will further expand to include Big Data tools such as Apache Hadoop ecosystem, HDFS and MapReduce frameworks. Also other R compatible tools such as Apache Spark, its machine learning library Spark MLlib, as well as H2O. Style and approach This book will serve as a practical guide to tackling Big Data problems using R programming language and its statistical environment. Each section of the book will present you with concise and easy-to-follow steps on how to process, transform and analyse large data sets.
R Mining Spatial Text Web And Social Media Data
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Author : Bater Makhabel
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-06-19
R Mining Spatial Text Web And Social Media Data written by Bater Makhabel and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-19 with Computers categories.
Create data mining algorithms About This Book Develop a strong strategy to solve predictive modeling problems using the most popular data mining algorithms Real-world case studies will take you from novice to intermediate to apply data mining techniques Deploy cutting-edge sentiment analysis techniques to real-world social media data using R Who This Book Is For This Learning Path is for R developers who are looking to making a career in data analysis or data mining. Those who come across data mining problems of different complexities from web, text, numerical, political, and social media domains will find all information in this single learning path. What You Will Learn Discover how to manipulate data in R Get to know top classification algorithms written in R Explore solutions written in R based on R Hadoop projects Apply data management skills in handling large data sets Acquire knowledge about neural network concepts and their applications in data mining Create predictive models for classification, prediction, and recommendation Use various libraries on R CRAN for data mining Discover more about data potential, the pitfalls, and inferencial gotchas Gain an insight into the concepts of supervised and unsupervised learning Delve into exploratory data analysis Understand the minute details of sentiment analysis In Detail Data mining is the first step to understanding data and making sense of heaps of data. Properly mined data forms the basis of all data analysis and computing performed on it. This learning path will take you from the very basics of data mining to advanced data mining techniques, and will end up with a specialized branch of data mining—social media mining. You will learn how to manipulate data with R using code snippets and how to mine frequent patterns, association, and correlation while working with R programs. You will discover how to write code for various predication models, stream data, and time-series data. You will also be introduced to solutions written in R based on R Hadoop projects. Now that you are comfortable with data mining with R, you will move on to implementing your knowledge with the help of end-to-end data mining projects. You will learn how to apply different mining concepts to various statistical and data applications in a wide range of fields. At this stage, you will be able to complete complex data mining cases and handle any issues you might encounter during projects. After this, you will gain hands-on experience of generating insights from social media data. You will get detailed instructions on how to obtain, process, and analyze a variety of socially-generated data while providing a theoretical background to accurately interpret your findings. You will be shown R code and examples of data that can be used as a springboard as you get the chance to undertake your own analyses of business, social, or political data. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Learning Data Mining with R by Bater Makhabel R Data Mining Blueprints by Pradeepta Mishra Social Media Mining with R by Nathan Danneman and Richard Heimann Style and approach A complete package with which will take you from the basics of data mining to advanced data mining techniques, and will end up with a specialized branch of data mining—social media mining.
Cybersecurity And Data Science Innovations For Sustainable Development Of Heicc
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Author : Thangavel Murugan
language : en
Publisher: CRC Press
Release Date : 2025-01-30
Cybersecurity And Data Science Innovations For Sustainable Development Of Heicc written by Thangavel Murugan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-30 with Computers categories.
Cybersecurity and Data Science Innovations for Sustainable Development of HEICC: Healthcare, Education, Industry, Cities, and Communities brings together a collection of chapters that explore the intersection of cybersecurity, data science, and sustainable development across key sectors: healthcare, education, industry, cities, and communities. It delves into cybersecurity advancements and examines how innovations in cybersecurity are shaping the landscape of healthcare, education, industry, and urban environments. Data science advancements take center stage, showcasing the transformative power of data analytics in improving outcomes across HEICC sectors. Whether it’s optimizing resource allocation in healthcare, protecting patient privacy, personalizing learning experiences in education, enhancing efficiency in industry, or fostering sustainable development in cities and communities, data science offers unprecedented opportunities for innovation and progress. Key points: Healthcare system security and privacy, protecting patient data, and enabling development of novel healthcare solutions Securing educational data, improving online learning security, and harnessing data analytics for tailored education approaches Manufacturing, finance, and transportation. Diving into critical infrastructure security, detecting and mitigating cyber threats, and using data‐driven insights for better industrial operations Helping cities and communities develop sustainably, smart city security challenges, data privacy in urban environments, data analytics for urban planning, and community cybersecurity awareness This book serves as a comprehensive guide for researchers, practitioners, policymakers, and stakeholders navigating the complex landscape of cybersecurity and data science in the pursuit of sustainable development across HEICC domains.
Oracle R Enterprise Harnessing The Power Of R In Oracle Database
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Author : Brendan Tierney
language : en
Publisher: McGraw Hill Professional
Release Date : 2016-11-04
Oracle R Enterprise Harnessing The Power Of R In Oracle Database written by Brendan Tierney and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-04 with Computers categories.
Master the Big Data Capabilities of Oracle R Enterprise Effectively manage your enterprise’s big data and keep complex processes running smoothly using the hands-on information contained in this Oracle Press guide. Oracle R Enterprise: Harnessing the Power of R in Oracle Database shows, step-by-step, how to create and execute large-scale predictive analytics and maintain superior performance. Discover how to explore and prepare your data, accurately model business processes, generate sophisticated graphics, and write and deploy powerful scripts. You will also find out how to effectively incorporate Oracle R Enterprise features in APEX applications, OBIEE dashboards, and Apache Hadoop systems. Learn to: • Install, configure, and administer Oracle R Enterprise • Establish connections and move data to the database • Create Oracle R Enterprise packages and functions • Use the R language to work with data in Oracle Database • Build models using ODM, ORE, and other algorithms • Develop and deploy R scripts and use the R script repository • Execute embedded R scripts and employ ORE SQL API functions • Map and manipulate data using Oracle R Advanced Analytics for Hadoop • Use ORE in Oracle Data Miner, OBIEE, and other applications