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Applied Data Mining: Statistical Methods for Business and Industry (Statistics in Practice)
Applied Data Mining: Statistical Methods for Business and Industry (Statistics in Practice)

Data mining can be defined as the process of selection, exploration and modelling of large databases, in order to discover models and patterns. The increasing availability of data in the current information society has led to the need for valid tools for its modelling and analysis. Data mining and applied statistical methods are the...

Practical Forensic Imaging: Securing Digital Evidence with Linux Tools
Practical Forensic Imaging: Securing Digital Evidence with Linux Tools

Forensic image acquisition is an important part of postmortem incident response and evidence collection. Digital forensic investigators acquire, preserve, and manage digital evidence to support civil and criminal cases; examine organizational policy violations; resolve disputes; and analyze cyber attacks.

Practical
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Visual Six Sigma: Making Data Analysis Lean (Wiley and SAS Business Series)
Visual Six Sigma: Making Data Analysis Lean (Wiley and SAS Business Series)
Streamline data analysis with an intuitive, visual Six Sigma strategy

Visual Six Sigma provides the statistical techniques that help you get more information from your data. A unique emphasis on the visual allows you to take a more active role in data-driven decision making, so you can leverage your contextual...

Data Mining and Statistics for Decision Making
Data Mining and Statistics for Decision Making
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 usually associated with a business or an organization's need to identify...
Practical Web Scraping for Data Science: Best Practices and Examples with Python
Practical Web Scraping for Data Science: Best Practices and Examples with Python

This book provides a complete and modern guide to web scraping, using Python as the programming language, without glossing over important details or best practices. Written with a data science audience in mind, the book explores both scraping and the larger context of web technologies in which it operates, to ensure full...

Applying Predictive Analytics: Finding Value in Data
Applying Predictive Analytics: Finding Value in Data

This textbook presents a practical approach to predictive analytics for classroom learning. It focuses on using analytics to solve business problems and compares several different modeling techniques, all explained from examples using the SAS Enterprise Miner software. The authors demystify complex algorithms to show how they can be...

The Cloud-Based Demand-Driven Supply Chain (Wiley and SAS Business Series)
The Cloud-Based Demand-Driven Supply Chain (Wiley and SAS Business Series)

It’s time to get your head in the cloud!

In today’s business environment, more and more people are requesting cloud-based solutions to help solve their business challenges. So how can you not only anticipate your clients’ needs but also keep ahead of the curve to ensure their goals stay on...

Practical R 4: Applying R to Data Manipulation, Processing and Integration
Practical R 4: Applying R to Data Manipulation, Processing and Integration

Get started with an accelerated introduction to the R ecosystem, programming language, and tools including R script and RStudio. Utilizing many examples and projects, this book teaches you how to get data into R and how to work with that data using R. Once grounded in the fundamentals, the rest of Practical R...

 
   
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