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R for Business Analytics
R for Business Analytics

R for Business Analytics looks at some of the most common tasks performed by business analysts and helps the user navigate the wealth of information in R and its 4000 packages.  With this information the reader can select the packages that can help process the analytical tasks with minimum effort and maximum usefulness. The use of...

Pattern Recognition and Classification: An Introduction
Pattern Recognition and Classification: An Introduction

The use of pattern recognition and classification is fundamental to many of the automated electronic systems in use today. However, despite the existence of a number of notable books in the field, the subject remains very challenging, especially for the beginner.

Pattern Recognition and Classification presents a comprehensive...

Data Mining and Business Analytics with R
Data Mining and Business Analytics with R

Collecting, analyzing, and extracting valuable information froma large amount of data requires easily accessible, robust,computational and analytical tools. Data Mining and BusinessAnalytics with R utilizes the open source software R for theanalysis, exploration, and simplification of large high-dimensionaldata sets. As a result, readers are...

Graphing Data with R: An Introduction
Graphing Data with R: An Introduction

It’s much easier to grasp complex data relationships with a graph than by scanning numbers in a spreadsheet. This introductory guide shows you how to use the R language to create a variety of useful graphs for visualizing and analyzing complex data for science, business, media, and many other fields. You’ll learn methods...

DevOps with Kubernetes: Accelerating software delivery with container orchestrators
DevOps with Kubernetes: Accelerating software delivery with container orchestrators

Learn to implement DevOps using Docker & Kubernetes.

About This Book

  • Learning DevOps, container, and Kubernetes within one book.
  • Leverage Kubernetes as a platform to deploy, scale, and run containers efficiently.
  • A practical guide towards container management and...
Java: Data Science Made Easy
Java: Data Science Made Easy

Data collection, processing, analysis, and more

About This Book

  • Your entry ticket to the world of data science with the stability and power of Java
  • Explore, analyse, and visualize your data effectively using easy-to-follow examples
  • A highly practical course covering a broad...
Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning
Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning

This practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. If you’re comfortable with Python and its libraries, including pandas and scikit-learn, you’ll be able to address specific problems such as loading data, handling text or...

Learning Predictive Analytics with Python: Gain practical insights into predictive modelling by implementing Predictive Analytics algorithms on public datasets with Python
Learning Predictive Analytics with Python: Gain practical insights into predictive modelling by implementing Predictive Analytics algorithms on public datasets with Python

Gain practical insights into predictive modelling by implementing Predictive Analytics algorithms on public datasets with Python

About This Book

  • A step-by-step guide to predictive modeling including lots of tips, tricks, and best practices
  • Get to grips with the basics of Predictive...
Mastering Windows Server 2016
Mastering Windows Server 2016
The IT pro's must-have guide to Windows Server 2016

Mastering Windows Server 2016 is a complete resource for IT professionals needing to get quickly up to date on the latest release. Designed to provide comprehensive information in the context of real-world usage, this book offers expert guidance through the new...

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...
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)

This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of colour graphics. It is a valuable resource...

Computational Social Network Analysis: Trends, Tools and Research Advances (Computer Communications and Networks)
Computational Social Network Analysis: Trends, Tools and Research Advances (Computer Communications and Networks)

Social networks provide a powerful abstraction of the structure and dynamics of diverse kinds of people or people-to-technology interaction. Web 2.0 has enabled a new generation of web-based communities, social networks, and folksonomies to facilitate collaboration among different communities.

This unique text/reference compares...

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