Data mining

The vast majority of Oracle SQL books discuss some syntax, provide the barest rudiments of using Oracle SQL, and perhaps include a few simple examples.

Sometimes the simplest answer is the best.

Despite its wide availability and usage, few developers and DBAs have mastered the true power of Oracle SQLPlus.

The Internet, with its profusion of information, has made us hungry for ever more, ever better data.

A comprehensive guide for IoT engineers, this book integrates data science, machine learning, and systems analytics to provide a robust understanding of modern techniques.

This book is dedicated to exploring and explaining time series event detection in databases.

Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge.

Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge.

Graphical models are of increasing importance in applied statistics, and in particular in data mining.

The increasing availability of data in our current, information overloaded society has led to the need for valid tools for its modelling and analysis.

Based around eleven international real life case studies and including contributions from leading experts in the field this groundbreaking book explores the need for the grid-enabling of data mining applications and provides a comprehensive study of the technology, techniques and management skills necessary to create them.

Text Mining: Applications and Theory presents the state-of-the-art algorithms for text mining from both the academic and industrial perspectives.

This is an applied handbook for the application of data mining techniques in the CRM framework.

Data Mining for Genomics and Proteomics uses pragmatic examples and a complete case study to demonstrate step-by-step how biomedical studies can be used to maximize the chance of extracting new and useful biomedical knowledge from data.

Understand how to use the new features of Microsoft SQL Server 2008 for data mining by using the tools in Data Mining with Microsoft SQL Server 2008, which will show you how to use the SQL Server Data Mining Toolset with Office 2007 to mine and analyze data.

A hands-on guide to making valuable decisions from data using advanced data mining methods and techniques This second installment in the Making Sense of Data series continues to explore a diverse range of commonly used approaches to making and communicating decisions from data.

Provides readers with the methods, algorithms, and means to perform text mining tasks This book is devoted to the fundamentals of text mining using Perl, an open-source programming tool that is freely available via the Internet (www.

The most thorough and up-to-date introduction to data mining techniques using SAS Enterprise Miner.

Using data from one season of NBA games, Basketball Data Science: With Applications in R is the perfect book for anyone interested in learning and applying data analytics in basketball.

Using data from one season of NBA games, Basketball Data Science: With Applications in R is the perfect book for anyone interested in learning and applying data analytics in basketball.

This volume brings together research and system designs that address the scientific basis and the practical systems design issues that support areas ranging from intelligent business interfaces and predictive analytics to economics modeling.

This volume brings together research and system designs that address the scientific basis and the practical systems design issues that support areas ranging from intelligent business interfaces and predictive analytics to economics modeling.

This book serves as a current resource for Photoplethysmogram (PPG) signal analysis using MATLAB(R).

This book serves as a current resource for Photoplethysmogram (PPG) signal analysis using MATLAB(R).

Large data sets arriving at every increasing speeds require a new set of efficient data analysis techniques.

Large data sets arriving at every increasing speeds require a new set of efficient data analysis techniques.

This book provides comprehensive details of all Swarm Intelligence based Techniques available till date in a comprehensive manner along with their mathematical proofs.

This book provides comprehensive details of all Swarm Intelligence based Techniques available till date in a comprehensive manner along with their mathematical proofs.

Statistical Learning using Neural Networks: A Guide for Statisticians and Data Scientists with Python introduces artificial neural networks starting from the basics and increasingly demanding more effort from readers, who can learn the theory and its applications in statistical methods with concrete Python code examples.

Statistical Learning using Neural Networks: A Guide for Statisticians and Data Scientists with Python introduces artificial neural networks starting from the basics and increasingly demanding more effort from readers, who can learn the theory and its applications in statistical methods with concrete Python code examples.

Data Analytics Applied to the Mining Industry describes the key challenges facing the mining sector as it transforms into a digital industry able to fully exploit process automation, remote operation centers, autonomous equipment and the opportunities offered by the industrial internet of things.

Data Analytics Applied to the Mining Industry describes the key challenges facing the mining sector as it transforms into a digital industry able to fully exploit process automation, remote operation centers, autonomous equipment and the opportunities offered by the industrial internet of things.

This handbook addresses how smart operations, management, and healthcare can be used to detect and analyze supply chain problems, business problems, and diseases.

Healthcare transformation requires us to continually look at new and better ways to manage insights - both within and outside the organization.

Healthcare transformation requires us to continually look at new and better ways to manage insights - both within and outside the organization.

Big Data Systems encompass massive challenges related to data diversity, storage mechanisms, and requirements of massive computational power.

Scientists often collect samples of curves and other functional observations, and develop models where parameters are also functions.

Computational inference has taken its place alongside asymptotic inference and exact techniques in the standard collection of statistical methods.

Comparing Distributions refers to the statistical data analysis that encompasses the traditional goodness-of-fit testing.

This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework.

Many networked computer systems are far too vulnerable to cyber attacks that can inhibit their functioning, corrupt important data, or expose private information.

Data Mining in Agriculture represents a comprehensive effort to provide graduate students and researchers with an analytical text on data mining techniques applied to agriculture and environmental related fields.

The explosive growth of e-commerce and online environments has made the issue of information search and selection increasingly serious; users are overloaded by options to consider and they may not have the time or knowledge to personally evaluate these options.

In recent years there has been an explosion of network data - that is, measu- ments that are either of or from a system conceptualized as a network - from se- ingly all corners of science.

Data Mining for Business Applications presents the state-of-the-art research and development outcomes on methodologies, techniques, approaches and successful applications in the area.

Every mathematical discipline goes through three periods of development: the naive, the formal, and the critical.

One of the "e;image"e; problems with wavelets is that because they have been a dominant area of interest (in nonparametric smoothing) people have forgotten that they are general tools with a fascinating role and future in other areas.

Remarkable advances in computation and data storage and the ready availability of huge data sets have been the keys to the growth of the new disciplines of data mining and machine learning, while the enormous success of the Human Genome Project has opened up the field of bioinformatics.

Social computing concerns the study of social behavior and context based on computational systems.

The use of geospatial technologies has become ubiquitous since the leading Internet vendors delivered a number of popular map websites.