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2014
EN
Decision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining; it is the science of exploring large and complex bodies of data in order to discover useful patterns. Decision tree learning continues to evolve over time. Existing methods are constantly being improved and new methods introduced.This 2nd Edition is dedicated entirely to the field of decision trees in data mining; to cover all aspects of this important technique, as well as im...
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Data Analysis with Open Source Tools
A Hands-On Guide for Programmers and Data Scientists
2010
EN
Collecting data is relatively easy, but turning raw information into something useful requires that you know how to extract precisely what you need. With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through...
2013
EN
Big Data Analytics with R and Hadoop is a tutorial style book that focuses on all the powerful big data tasks that can be achieved by integrating R and Hadoop.This book is ideal for R developers who are looking for a way to perform big data analytics with Hadoop. This book is also aimed at those who know Hadoop and want to build some intelligent applications over Big data with R packages. It would be helpful if readers have basic knowledge of R.
Apache Hadoop YARN
Moving beyond MapReduce and Batch Processing with Apache Hadoop 2
2014
EN
“This book is a critically needed resource for the newly released Apache Hadoop 2.0, highlighting YARN as the significant breakthrough that broadens Hadoop beyond the MapReduce paradigm.” —From the Foreword by Raymie Stata, CEO of Altiscale The Insider’s Guide to Building Distributed, Big Data Applications with Apache Hadoop™ YARN Apache Hadoop is helping...
Data Analysis with R
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2015
EN
Load, wrangle, and analyze your data using the world\\'s most powerful statistical programming languageKey Features\[\*\]Load, manipulate and analyze data from different sources\[\*\]Gain a deeper understanding of fundamentals of applied statistics\[\*\]A practical guide to performing data analysis in practiceBook DescriptionFrequently the tool of choice for academics, R has spread deep into the private sector and can be foun...
Machine Learning
An Algorithmic Perspective, Second Edition
2014
EN
Accessible
A Proven, Hands-On Approach for Students without a Strong Statistical FoundationSince the best-selling first edition was published, there have been several prominent developments in the field of machine learning, including the increasing work on the statistical interpretations of machine learning algorithms. Unfortunately, computer science students
How To Mine Bitcoin:
Learn How To Mine Cryptocurrency
2017
EN
How to get your start in Bitcoin investing or mining.Here You will learn the tools of the trade and be shown how to use them on an entry level.I want people to know how to use these tools to benefit themselves. IT is not that hard to get into mining, but it is an investment to get into. The world of Cryptocurrency is hard and ever changing, but it is a good thing to know. So welcome to the first class on Cryptocurrency.Get your copy today, J...
2013
EN
Collecting, analyzing, and extracting valuable information from a large amount of data requires easily accessible, robust, computational and analytical tools. Data Mining and Business Analytics with R utilizes the open source software R for the analysis, exploration, and simplification of large high-dimensional data sets. As a result, readers are provided with the needed guidance to model and interpret complicated data and become adept at building powerful models for prediction an...
Scalable Pattern Recognition Algorithms
Applications in Computational Biology and Bioinformatics
2014
EN
This book addresses the need for a unified framework describing how soft computing and machine learning techniques can be judiciously formulated and used in building efficient pattern recognition models. The text reviews both established and cutting-edge research, providing a careful balance of theory, algorithms, and applications, with a particular emphasis given to applications in computational biology and bioinformatics. Features: integrates different soft computing and machine learning...
2014
EN
This book is intended for developers and Big Data engineers who want to know all about HBase at a hands-on level. For in-depth understanding, it would be helpful to have a bit of familiarity with HDFS and MapReduce programming concepts with no prior experience with HBase or similar technologies. This book is also for Big Data enthusiasts and database developers who have worked with other NoSQL databases and now want to explore HBase as another futuristic, scalable database solution in the ...
2016
EN
Unlock the power of your data with Hadoop 2.X ecosystem and its data warehousing techniques across large data setsAbout This BookConquer the mountain of data using Hadoop 2.X toolsThe authors succeed in creating a context for Hadoop and its ecosystemHands-on examples and recipes giving the bigger picture and helping you to master Hadoop 2.X data processing platformsOvercome the challenging data processing problems using...











