Python Data Science Handbook

Describes the features of the Python programming language's networking capabilities, covering such topics as sockets, network servers, Web client access, HTML and XHTML parsing, email composition, and

This issue delivers concrete suggestions for optimally using data visualization in evaluation, as well as suggestions for best practices in data visualization design. It focuses on specific quantitati

"This book highlights entirely new and detailed spatial-temporal micro-simulation methodologies for human mobility and the emerging dynamics of our society, offering novel ideas grounded in big data f

Pro iOS Persistence explains how to build apps in Objective-C and Swiftthat persist and use data most effectively including the popular Core Data framework. Covering common and advanced persistence pa

'Big data' poses challenges that require both classical multivariate methods and contemporary techniques from machine learning and engineering. This modern text equips you for the new world - integrating the old and the new, fusing theory and practice and bridging the gap to statistical learning. The theoretical framework includes formal statements that set out clearly the guaranteed 'safe operating zone' for the methods and allow you to assess whether data is in the zone, or near enough. Extensive examples showcase the strengths and limitations of different methods with small classical data, data from medicine, biology, marketing and finance, high-dimensional data from bioinformatics, functional data from proteomics, and simulated data. High-dimension low-sample-size data gets special attention. Several data sets are revisited repeatedly to allow comparison of methods. Generous use of colour, algorithms, Matlab code, and problem sets complete the package. Suitable for master's/graduat

The first handbook to provide a state-of-the-art overview of the whole field of QDA, and a must-have for all qualitative researchers

Large-scale data analysis ("Big Data") is suddenly of crucial importance to virtually every enterprise. Mobile and social technologies are generating massive datasets, and distributed cloud computing

Pattern recognition in data is a well known classical problem that falls under the ambit of data analysis. As we need to handle different data, the nature of patterns, their recognition and the types

Molecular biology is undergoing exponential growth in both the volume and complexity of biological data. This book offers the first comprehensive overview of data mining, preprocessing, postprocessing

"Panel Data Analysis using EViews provides graduate students, researchers, and statisticians with step-by-step guidance on how to apply EViews software to panel data analysis using appropriate empiric

Computer vision is the science and technology of making machines that see. It is concerned with the theory, design and implementation of algorithms that can automatically process visual data to recogn

This brief provides methods for harnessing Twitter data to discover solutions to complex inquiries. The brief introduces the process of collecting data through Twitter’s APIs and offers strategies for

This volume tackles the conflicting requirements of data compression and indexing in massive datasets, by using optimization techniques to improve compression and reconfiguring data structure to incre

Data Security Breaches and Privacy in Europe aims to consider data protection and cybersecurity issues; more specifically, it aims to provide a fruitful discussion on data security breaches. A detaile

Providing the knowledge and practical experience to begin analysing scientific data, this book is ideal for physical sciences students wishing to improve their data handling skills. The book focuses on explaining and developing the practice and understanding of basic statistical analysis, concentrating on a few core ideas, such as the visual display of information, modelling using the likelihood function, and simulating random data. Key concepts are developed through a combination of graphical explanations, worked examples, example computer code and case studies using real data. Students will develop an understanding of the ideas behind statistical methods and gain experience in applying them in practice. Further resources are available at www.cambridge.org/9781107607590, including data files for the case studies so students can practise analysing data, and exercises to test students' understanding.

Owing to continuous advances in the computational power of handheld devices like smartphones and tablet computers, it has become possible to perform Big Data operations including modern data mining pr

Providing the knowledge and practical experience to begin analysing scientific data, this book is ideal for physical sciences students wishing to improve their data handling skills. The book focuses on explaining and developing the practice and understanding of basic statistical analysis, concentrating on a few core ideas, such as the visual display of information, modelling using the likelihood function, and simulating random data. Key concepts are developed through a combination of graphical explanations, worked examples, example computer code and case studies using real data. Students will develop an understanding of the ideas behind statistical methods and gain experience in applying them in practice. Further resources are available at www.cambridge.org/9781107607590, including data files for the case studies so students can practise analysing data, and exercises to test students' understanding.

To tackle the challenges of Big Data, novel approaches and tools have emerged. Moreover, the technology required for big-data computing is developing at a satisfactory rate due to market forces and te

Be part of the big learning data revolution!

"A chronological listing of the members of the British comedy group Monty Python, both as a group and individually. Coverage spans between 1969 (the year Monty Python's Flying Circus debuted) and 2012

Practical Data Analysis is a practical, step-by-step guide to empower small businesses to manage and analyze your data and extract valuable information from the data. This book is for developers, smal

An effective guide to geographic information systems and remote sensing analysis using Python 3About This BookConstruct applications for GIS development by exploiting PythonThis focuses on built-in Py

"This book discusses the exponential growth of information size and the innovative methods for data capture, storage, sharing, and analysis for big data"--

With emphasis firmly on such practical matters, this handbook sets forth clear guidelines for performing specific statistical tests with SPSS and interpreting the output. All chapters include the full

This introduction to the world of statistics covers exploratory data analysis, methods for collecting data, formal statistical inference, and techniques of regression and analysis of variance. 1983 ed

This book introduces the basic aspects of applied mathematics. It also covers such topics as information data manipulation, information coding, data approximation, data dimensionality reduction, data

This book covers the fundamental concepts in signal processing illustrated with Python code and made available via IPython Notebooks, which are live, interactive, browser-based documents that allow on

The field of data mining has made significant and far-reaching advances over the past three decades. Because of its potential power for solving complex problems, data mining has been successfully appl

Do you communicate data and information to stakeholders? This issue is Part 1 of a two-part series on data visualization and evaluation. In Part 1, we introduce recent developments in the quantitative

Python is the perfect “first programming language.” It’s easy for beginners to read and understand, and since it’s so widely used, you can apply what you’ve learned practically anywhere. Now, there’s

This guide details the use of the data analysis software R in political science. It explains the use of R for constructing descriptions of variables and performing substantive analysis of political re

Exceptionally clear and well-written chapters provide engaging discussions of the methods of accessing, generating, and analyzing social science data, using methods ranging from reflexive historical a

This report for data analysts is authored by the National Research Council's Committee on the Analysis of Massive Data; the Committee on Applied and Theoretical Statistics; the Board on Mathematical S

Explains how to use data analysis and data driven marketing to better understand a customer base, develop smarter marketing strategies, and accurately measure the impact of marketing campaigns.

Leverage big data to add value to your businessSocial media analytics, web-tracking, and other technologies help companies acquire and handle massive amounts of data to better understand their custome

Offered as an introduction to the field of data structures andalgorithms, Open Data Structures covers the implementation andanalysis of data structures for sequences (lists), queues, priorityqueues, u

A straightforward, full-color guide to showcasing data so your audience can see what you mean, not just read about itBig data is big news! Every company, industry, not-for-profit, and government agenc

Exceptionally clear and well-written chapters provide engaging discussions of the methods of accessing, generating, and analyzing social science data, using methods ranging from reflexive historical a

The Springer Handbook of Nanomaterials covers the description of materials which have dimension on the "nanoscale". The description of the nanomaterials in this Handbook follows the thorough but conci

Learning to program is one of the best investments that you can make for your research and your career. Python for biologists is a complete programming course for beginners that will give you the skil