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Intel Xeon Phi Coprocessor Architecture and Tools: The Guide for Application Developers (Expert's Voice in Microprocessors)
Intel Xeon Phi Coprocessor Architecture and Tools: The Guide for Application Developers (Expert's Voice in Microprocessors)

Intel® Xeon Phi™ Coprocessor Architecture and Tools: The Guide for Application Developers provides developers a comprehensive introduction and in-depth look at the Intel Xeon Phi coprocessor architecture and the corresponding parallel data structure tools and...

Element Stamp Algorithm for Matrix Formulation of Symbolic Circuits (Computer Networks)
Element Stamp Algorithm for Matrix Formulation of Symbolic Circuits (Computer Networks)
The need to analyze a linear network is a recurring requirement in computer-aided network analysis. Not only a majority of the network problems to be solved is posed as linear problems; nonlinear resistive and dynamic networks are usually solved by the analysis of a sequence of “linearized” networks. The analysis of...
Thoughtful Machine Learning: A Test-Driven Approach
Thoughtful Machine Learning: A Test-Driven Approach

Learn how to apply test-driven development (TDD) to machine-learning algorithms—and catch mistakes that could sink your analysis. In this practical guide, author Matthew Kirk takes you through the principles of TDD and machine learning, and shows you how to apply TDD to several machine-learning algorithms, including Naive...

Distances and Similarities in Intuitionistic Fuzzy Sets (Studies in Fuzziness and Soft Computing)
Distances and Similarities in Intuitionistic Fuzzy Sets (Studies in Fuzziness and Soft Computing)

This book presents the state-of-the-art in theory and practice regarding similarity and distance measures for intuitionistic fuzzy sets. Quantifying similarity and distances is crucial for many applications, e.g. data mining, machine learning, decision making, and control. The work provides readers with a comprehensive set of theoretical...

Machine Learning with R - Second Edition
Machine Learning with R - Second Edition

Key Features

  • Harness the power of R for statistical computing and data science
  • Explore, forecast, and classify data with R
  • Use R to apply common machine learning algorithms to real-world scenarios

Book Description

Machine learning, at its core, is concerned...

Mastering Probabilistic Graphical Models using Python
Mastering Probabilistic Graphical Models using Python

Master probabilistic graphical models by learning through real-world problems and illustrative code examples in Python

About This Book

  • Gain in-depth knowledge of Probabilistic Graphical Models
  • Model time-series problems using Dynamic Bayesian Networks
  • A practical guide to...
Euclidean Shortest Paths: Exact or Approximate Algorithms
Euclidean Shortest Paths: Exact or Approximate Algorithms

This unique text/reference reviews algorithms for the exact or approximate solution of shortest-path problems, with a specific focus on a class of algorithms called rubberband algorithms. Discussing each concept and algorithm in depth, the book includes mathematical proofs for many of the given statements. Topics and features: provides...

Mastering SQL Server 2014 Data Mining
Mastering SQL Server 2014 Data Mining

Master selecting, applying, and deploying data mining models to build powerful predictive analysis frameworks

About This Book

  • Understand the different phases of data mining, along with the tools used at each stage
  • Explore the different data mining algorithms in depth
  • Become...
A Mathematical Tapestry: Demonstrating the Beautiful Unity of Mathematics
A Mathematical Tapestry: Demonstrating the Beautiful Unity of Mathematics

This easy-to-read book demonstrates how a simple geometric idea reveals fascinating connections and results in number theory, the mathematics of polyhedra, combinatorial geometry, and group theory. Using a systematic paper-folding procedure it is possible to construct a regular polygon with any number of sides. This remarkable algorithm has...

Architectures for Baseband Signal Processing
Architectures for Baseband Signal Processing

This book addresses challenges faced by both the algorithm designer and the chip designer, who need to deal with the ongoing increase of algorithmic complexity and required data throughput for today’s mobile applications. The focus is on implementation aspects and implementation constraints of individual components that are needed in...

Learning Apache Mahout Classification
Learning Apache Mahout Classification

Build and personalize your own classifiers using Apache Mahout

About This Book

  • Explore the different types of classification algorithms available in Apache Mahout
  • Create and evaluate your own ready-to-use classification models using real world datasets
  • A practical guide to...
Pentaho for Big Data Analytics
Pentaho for Big Data Analytics

With your knowledge of Java and this guide, you can take the analysis of your big data to new levels using Pentaho. Covers all the essentials tools, techniques, tips, and tricks in one handy volume.

Overview

  • A guide to using Pentaho Business Analytics for big data analysis
  • Learn...
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