Practical Data Processing and Analysis Using R

Gain insights into image-processing methodologies and algorithms, using machine learning and neural networks in Python. This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts that will be useful for implementing the algorithms discussed in the book. You will then cover all the core image processing algorithms in detail before moving onto the biggest computer vision library: OpenCV. You’ll see the OpenCV algorithms and how to use them for image processing. The next section looks at advanced machine learning and deep learning methods for image processing and classification. You’ll work with concepts such as pulse coupled neural networks, AdaBoost, XG boost, and convolutional neural networks for image-specific applications. Later you’ll explore how models are made in real time and then deployed using various DevOps tools. All the concepts in Practical Machine Learning and Image Processing are explained using r

Written in lucid language, this valuable textbook brings together fundamental concepts of data mining and data warehousing in a single volume. Important topics including information theory, decision tree, Naïve Bayes classifier, distance metrics, partitioning clustering, associate mining, data marts and operational data store are discussed comprehensively. The textbook is written to cater to the needs of undergraduate students of computer science, engineering and information technology for a course on data mining and data warehousing. The text simplifies the understanding of the concepts through exercises and practical examples. Chapters such as classification, associate mining and cluster analysis are discussed in detail with their practical implementation using Weka and R language data mining tools. Advanced topics including big data analytics, relational data models and NoSQL are discussed in detail. Pedagogical features including unsolved problems and multiple-choice questions are

本書《R語言與資料分析實戰》以R語言的「程式設計屬性」為中心，內容涵蓋R語言基礎理論到實際資料分析，透過分析模型和演算法等更實用的範例，講解了資料視覺化、統計分析、資料採擷、機器學習等常用的方法。同時書中還收錄了作者的實戰經驗和學習體會，可以解決資料統計分析過程中出現的各種問題。如果你是一名資料統計分析的研究人員，本書將是一本不可多得的參考書，能夠深化理解與認識R軟體的應用，進一步提高資料統計分析

Across the social sciences there has been increasing focus on reproducibility, i.e., the ability to examine a study's data and methods to ensure accuracy by reproducing the study. Reproducible Econome

Data-intensive systems are a technological building block supporting Big Data and Data Science applications.This book familiarizes readers with core concepts that they should be aware of before contin

Look at Python from a data science point of view and learn proven techniques for data visualization as used in making critical business decisions. Starting with an introduction to data science with Py

"This book outlines the overview of the Big data. It presents the big data components organized as four layers such as: big data sources, data massaging and store layer, analysis layer, and consumptio

This book offers new transparent views and step-by-step methods for performance evaluation of a set of units using Data Envelopment Analysis (DEA). The book has twelve practical chapters. Elementary c

Analysis of Clinical Trials Using SAS®: A Practical Guide, Second Edition bridges the gap between modern statistical methodology and real-world clinical trial applications. Tutorial material and step-

Engaging and accessible, this book teaches readers how to use inferential statistical thinking to check their assumptions, assess evidence about their beliefs, and avoid overinterpreting results that

Engaging and accessible, this book teaches readers how to use inferential statistical thinking to check their assumptions, assess evidence about their beliefs, and avoid overinterpreting results that

Master functions and discover how to write functional programs in R. In this concise book, you'll make your functions pure by avoiding side-effects; you’ll write functions that manipulate other functi

This introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical method

A practical guide to the analysis of models in mathematical biology and the biomedical sciences, this book utilizes MATLAB® to investigate the methodology for collecting, visualizing, and analyzing ex

This book provides hands-on tutorials with just the right amount of conceptual and motivational material to illustrate how to use the intuitive interface for data analysis in JMP. Each chapter feature

This book presents an overview of computational and statistical design and analysis of mass spectrometry-based proteomics, metabolomics, and lipidomics data. This contributed volume provides an introd

This book is a comprehensive introduction to financial modeling that teaches advanced undergraduate and graduate students in finance and economics how to use R to analyze financial data and implement

This contemporary presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The authors demonstrate how to analyze data—showi

Statistics at the Bench in R is a convenient bench-side handbook for biologists, designed as a handy reference guide for elementary and intermediate statistical analyses using the free/public software

Doing Sociolinguistics: A practical guide to data collection and analysis provides an accessible introduction and guide to the methods of data collection and analysis in the field of sociolinguistics.

Doing Sociolinguistics: A practical guide to data collection and analysis provides an accessible introduction and guide to the methods of data collection and analysis in the field of sociolinguistics.

Providing a practical, hands-on introduction to data conceptualization, measurement and association, this book gives students step-by-step instruction on data analysis using the latest version of SPSS

This book includes step-by-step examples and case studies that teach users the many power tricks for analyzing data in Excel. These tips have been honed by Oz du Soleil, a former financial analyst cha

Matthias Kaeding discusses Bayesian methods for analyzing discrete and continuous failure times where the effect of time and/or covariates is modeled via P-splines and additional basic function expans

If you are a data analyst who has a firm grip on some advanced data analysis techniques and wants to learn how to leverage the features of R, this is the book for you. You should have some basic knowl

Nursing Research Using Data Analysis: Qualitative Designs and Methods in Nursing is one book in a series of seven volumes that presents concise, how-to guides to conducting qualitative research -- for

Over the past four decades, the technology in vibration instrumentation & measurements, signal processing, and analytical simulation using finite element methods has advanced significantly. This b

There is an explosion of interest in Bayesian statistics, primarily because recently created computational methods have finally made Bayesian analysis obtainable to a wide audience. Doing Bayesian Dat

Control of electric drives requires transforming to dq-frame from a-b-c phase-domain. Most research literature and textbooks in this field treat dq-axis transformation of a-b-c phase quantities on a p

"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 surroundi

With a focus on the needs of educators and students, Making Sense of Data presents the steps and issues that need to be considered in order to successfully complete a data analysis or data mining proj

DEAFrontier Software Included

This book provides a complete analysis of educational production and costs using the nonparametric technique known as Data Envelopment Analysis (DEA). The book focuses on estimation of technical, allo

The book contains all the basic notions of Positron Emission Tomography that span from physiology to radiochemistry, physics, math and statistics. All material was carefully crafted and is now present

This highly practical handbook is an exhaustive treatment of eddy covariance measurement that will be of keen interest to scientists who are not necessarily specialists in micrometeorology. The chapte

In a world in which we are constantly surrounded by data, figures, and statistics, it is imperative to understand and to be able to use quantitative methods. Statistical models and methods are among t

The purpose of this book is to provide instruction and guidance on preparing quantitative data sets prior to answering a studyAs research questions. Preparation may involve data management and manipul

In order to protect company’s information assets such as sensitive customer records, health care records, etc., the security practitioner first needs to find out: what needs protected, what risks thos