Bad Data Handbook

Cleaning Up The Data So You Can Get Back To Work

Author: Q. Ethan McCallum

Publisher: "O'Reilly Media, Inc."

ISBN: 1449324975

Category: Computers

Page: 264

View: 7769


What is bad data? Some people consider it a technical phenomenon, like missing values or malformed records, but bad data includes a lot more. In this handbook, data expert Q. Ethan McCallum has gathered 19 colleagues from every corner of the data arena to reveal how they’ve recovered from nasty data problems. From cranky storage to poor representation to misguided policy, there are many paths to bad data. Bottom line? Bad data is data that gets in the way. This book explains effective ways to get around it. Among the many topics covered, you’ll discover how to: Test drive your data to see if it’s ready for analysis Work spreadsheet data into a usable form Handle encoding problems that lurk in text data Develop a successful web-scraping effort Use NLP tools to reveal the real sentiment of online reviews Address cloud computing issues that can impact your analysis effort Avoid policies that create data analysis roadblocks Take a systematic approach to data quality analysis

Applied Mathematics for the Analysis of Biomedical Data

Models, Methods, and MATLAB

Author: Peter J. Costa

Publisher: John Wiley & Sons

ISBN: 1119269490

Category: Mathematics

Page: 448

View: 3571


Features a practical approach to the analysis of biomedical data via mathematical methods and provides a MATLAB® toolbox for the collection, visualization, and evaluation of experimental and real-life data Applied Mathematics for the Analysis of Biomedical Data: Models, Methods, and MATLAB® presents a practical approach to the task that biological scientists face when analyzing data. The primary focus is on the application of mathematical models and scientific computing methods to provide insight into the behavior of biological systems. The author draws upon his experience in academia, industry, and government–sponsored research as well as his expertise in MATLAB to produce a suite of computer programs with applications in epidemiology, machine learning, and biostatistics. These models are derived from real–world data and concerns. Among the topics included are the spread of infectious disease (HIV/AIDS) through a population, statistical pattern recognition methods to determine the presence of disease in a diagnostic sample, and the fundamentals of hypothesis testing. In addition, the author uses his professional experiences to present unique case studies whose analyses provide detailed insights into biological systems and the problems inherent in their examination. The book contains a well-developed and tested set of MATLAB functions that act as a general toolbox for practitioners of quantitative biology and biostatistics. This combination of MATLAB functions and practical tips amplifies the book’s technical merit and value to industry professionals. Through numerous examples and sample code blocks, the book provides readers with illustrations of MATLAB programming. Moreover, the associated toolbox permits readers to engage in the process of data analysis without needing to delve deeply into the mathematical theory. This gives an accessible view of the material for readers with varied backgrounds. As a result, the book provides a streamlined framework for the development of mathematical models, algorithms, and the corresponding computer code. In addition, the book features: Real–world computational procedures that can be readily applied to similar problems without the need for keen mathematical acumen Clear delineation of topics to accelerate access to data analysis Access to a book companion website containing the MATLAB toolbox created for this book, as well as a Solutions Manual with solutions to selected exercises Applied Mathematics for the Analysis of Biomedical Data: Models, Methods, and MATLAB® is an excellent textbook for students in mathematics, biostatistics, the life and social sciences, and quantitative, computational, and mathematical biology. This book is also an ideal reference for industrial scientists, biostatisticians, product development scientists, and practitioners who use mathematical models of biological systems in biomedical research, medical device development, and pharmaceutical submissions.

Cognitive Computing: Theory and Applications

Author: Vijay V Raghavan,Venkat N. Gudivada,Venu Govindaraju,C.R. Rao

Publisher: Elsevier

ISBN: 0444637516

Category: Mathematics

Page: 404

View: 3745


Cognitive Computing: Theory and Applications, written by internationally renowned experts, focuses on cognitive computing and its theory and applications, including the use of cognitive computing to manage renewable energy, the environment, and other scarce resources, machine learning models and algorithms, biometrics, Kernel Based Models for transductive learning, neural networks, graph analytics in cyber security, neural networks, data driven speech recognition, and analytical platforms to study the brain-computer interface. Comprehensively presents the various aspects of statistical methodology Discusses a wide variety of diverse applications and recent developments Contributors are internationally renowned experts in their respective areas

Gestión de la información web usando Python

Author: Sarasa Cabezuelo, Antonio

Publisher: Editorial UOC

ISBN: 8491164863

Category: Computers

Page: 300

View: 1893


En este manual se realiza una introducción a un conjunto de herramientas y técnicas para el acceso y procesamiento de datos web, que se encuentran en formatos como XML, CSV o JSON, o bien en bases de datos tanto relacionales como NoSQL. El objetivo de esta obra es acercar al lector estos conocimientos a partir de las herramientas y librerías de un lenguaje de programación concreto como Python, el más utilizado hoy en el área del análisis de datos y big data. El primer capítulo constituye una introducción a Python, que sirve como lenguaje vehicular en el resto de los capítulos, los cuales se dedican a estudiar el acceso y procesamiento de datos en los formatos XML, JSON y CSV. Los siguientes capítulos abordan el acceso a bases de datos relacionales, SQLite y MySQL, y a la base de datos NoSQL MongoDB. En los dos últimos capítulos, se tratan técnicas de extracción de información usando web scraping y programación de páginas web con la framework Bottle. Cada capítulo contiene algunos ejercicios propuestos para fijar las ideas expuestas.

Code Complete

A Practical Handbook of Software Construction

Author: Steve McConnell,Steve M. McConnell

Publisher: N.A

ISBN: 9781556154843

Category: Computers

Page: 857

View: 3794


A practical guide to software design discusses the art and science of constructing software and provides examples in C, Pascal, BASIC, Fortran, and Ada, with a focus on successful programming techniques. Original.