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Mathematical Problems in Data Science

Overview of attention for book
Mathematical Problems in Data Science
Springer International Publishing

Table of Contents

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    Book Overview
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    Chapter 1 Introduction: Data Science and BigData Computing
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    Chapter 2 Overview of Basic Methods for Data Science
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    Chapter 3 Relationship and Connectivity of Incomplete Data Collection
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    Chapter 4 Machine Learning for Data Science: Mathematical or Computational
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    Chapter 5 Images, Videos, and BigData
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    Chapter 6 Topological Data Analysis
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    Chapter 7 Monte Carlo Methods and Their Applications in Big Data Analysis
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    Chapter 8 Feature Extraction via Vector Bundle Learning
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    Chapter 9 Curve Interpolation and Financial Curve Construction
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    Chapter 10 Advanced Methods in Variational Learning: Segmentation with Intensity Inhomogeneity
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    Chapter 11 An On-Line Strategy of Groups Evacuation from a Convex Region in the Plane
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    Chapter 12 A New Computational Model of Bigdata
Attention for Chapter 7: Monte Carlo Methods and Their Applications in Big Data Analysis
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