The Resource Data science with Java : practical methods for scientists and engineers, Michael R. Brzustowicz
Data science with Java : practical methods for scientists and engineers, Michael R. Brzustowicz
Resource Information
The item Data science with Java : practical methods for scientists and engineers, Michael R. Brzustowicz represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Missouri Libraries.This item is available to borrow from 2 library branches.
Resource Information
The item Data science with Java : practical methods for scientists and engineers, Michael R. Brzustowicz represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Missouri Libraries.
This item is available to borrow from 2 library branches.
 Extent
 1 online resource (233 pages)
 Note
 Includes index
 Contents

 Copyright; Table of Contents; Preface; Who Should Read This Book; Why I Wrote This Book; A Word on Data Science Today; Navigating This Book; Conventions Used in This Book; Using Code Examples; O'Reilly Safari; How to Contact Us; Acknowledgments; Chapter 1. Data I/O; What Is Data, Anyway?; Data Models; Univariate Arrays; Multivariate Arrays; Data Objects; Matrices and Vectors; JSON; Dealing with Real Data; Nulls; Blank Spaces; Parse Errors; Outliers; Managing Data Files; Understanding File Contents First; Reading from a Text File; Reading from a JSON File; Reading from an Image File
 Writing to a Text FileMastering Database Operations; CommandLine Clients; Structured Query Language; Java Database Connectivity; Visualizing Data with Plots; Creating Simple Plots; Plotting Mixed Chart Types; Saving a Plot to a File; Chapter 2. Linear Algebra; Building Vectors and Matrices; Array Storage; Block Storage; Map Storage; Accessing Elements; Working with Submatrices; Randomization; Operating on Vectors and Matrices; Scaling; Transposing; Addition and Subtraction; Length; Distances; Multiplication; Inner Product; Outer Product; Entrywise Product; Compound Operations
 Affine TransformationMapping a Function; Decomposing Matrices; Cholesky Decomposition; LU Decomposition; QR Decomposition; Singular Value Decomposition; Eigen Decomposition; Determinant; Inverse; Solving Linear Systems; Chapter 3. Statistics; The Probabilistic Origins of Data; Probability Density; Cumulative Probability; Statistical Moments; Entropy; Continuous Distributions; Discrete Distributions; Characterizing Datasets; Calculating Moments; Descriptive Statistics; Multivariate Statistics; Covariance and Correlation; Regression; Working with Large Datasets; Accumulating Statistics
 Merging StatisticsRegression; Using Builtin Database Functions; Chapter 4. Data Operations; Transforming Text Data; Extracting Tokens from a Document; Utilizing Dictionaries; Vectorizing a Document; Scaling and Regularizing Numeric Data; Scaling Columns; Scaling Rows; Matrix Scaling Operator; Reducing Data to Principal Components; Covariance Method; SVD Method; Creating Training, Validation, and Test Sets; IndexBased Resampling; ListBased Resampling; MiniBatches; Encoding Labels; A Generic Encoder; OneHot Encoding; Chapter 5. Learning and Prediction; Learning Algorithms
 Iterative Learning ProcedureGradient Descent Optimizer; Evaluating Learning Processes; Minimizing a Loss Function; Minimizing the Sum of Variances; Silhouette Coefficient; LogLikelihood; Classifier Accuracy; Unsupervised Learning; kMeans Clustering; DBSCAN; Gaussian Mixtures; Supervised Learning; Naive Bayes; Linear Models; Deep Networks; Chapter 6. Hadoop MapReduce; Hadoop Distributed File System; MapReduce Architecture; Writing MapReduce Applications; Anatomy of a MapReduce Job; Hadoop Data Types; Mappers; Reducers; The Simplicity of a JSON String as Text; Deployment Wizardry
 Isbn
 9781491934067
 Label
 Data science with Java : practical methods for scientists and engineers
 Title
 Data science with Java
 Title remainder
 practical methods for scientists and engineers
 Statement of responsibility
 Michael R. Brzustowicz
 Language
 eng
 Cataloging source
 N$T
 http://library.link/vocab/creatorName
 Brzustowicz, Michael R
 Dewey number
 005.133
 Illustrations
 illustrations
 Index
 index present
 LC call number
 QA76.73.J39
 Literary form
 non fiction
 Nature of contents
 dictionaries
 http://library.link/vocab/subjectName

 Java (Computer program language)
 Data structures (Computer science)
 COMPUTERS / Programming Languages / JavaScript
 Data structures (Computer science)
 Java (Computer program language)
 Label
 Data science with Java : practical methods for scientists and engineers, Michael R. Brzustowicz
 Note
 Includes index
 Antecedent source
 unknown
 Carrier category
 online resource
 Carrier category code

 cr
 Carrier MARC source
 rdacarrier
 Color
 multicolored
 Content category
 text
 Content type code

 txt
 Content type MARC source
 rdacontent
 Contents

 Copyright; Table of Contents; Preface; Who Should Read This Book; Why I Wrote This Book; A Word on Data Science Today; Navigating This Book; Conventions Used in This Book; Using Code Examples; O'Reilly Safari; How to Contact Us; Acknowledgments; Chapter 1. Data I/O; What Is Data, Anyway?; Data Models; Univariate Arrays; Multivariate Arrays; Data Objects; Matrices and Vectors; JSON; Dealing with Real Data; Nulls; Blank Spaces; Parse Errors; Outliers; Managing Data Files; Understanding File Contents First; Reading from a Text File; Reading from a JSON File; Reading from an Image File
 Writing to a Text FileMastering Database Operations; CommandLine Clients; Structured Query Language; Java Database Connectivity; Visualizing Data with Plots; Creating Simple Plots; Plotting Mixed Chart Types; Saving a Plot to a File; Chapter 2. Linear Algebra; Building Vectors and Matrices; Array Storage; Block Storage; Map Storage; Accessing Elements; Working with Submatrices; Randomization; Operating on Vectors and Matrices; Scaling; Transposing; Addition and Subtraction; Length; Distances; Multiplication; Inner Product; Outer Product; Entrywise Product; Compound Operations
 Affine TransformationMapping a Function; Decomposing Matrices; Cholesky Decomposition; LU Decomposition; QR Decomposition; Singular Value Decomposition; Eigen Decomposition; Determinant; Inverse; Solving Linear Systems; Chapter 3. Statistics; The Probabilistic Origins of Data; Probability Density; Cumulative Probability; Statistical Moments; Entropy; Continuous Distributions; Discrete Distributions; Characterizing Datasets; Calculating Moments; Descriptive Statistics; Multivariate Statistics; Covariance and Correlation; Regression; Working with Large Datasets; Accumulating Statistics
 Merging StatisticsRegression; Using Builtin Database Functions; Chapter 4. Data Operations; Transforming Text Data; Extracting Tokens from a Document; Utilizing Dictionaries; Vectorizing a Document; Scaling and Regularizing Numeric Data; Scaling Columns; Scaling Rows; Matrix Scaling Operator; Reducing Data to Principal Components; Covariance Method; SVD Method; Creating Training, Validation, and Test Sets; IndexBased Resampling; ListBased Resampling; MiniBatches; Encoding Labels; A Generic Encoder; OneHot Encoding; Chapter 5. Learning and Prediction; Learning Algorithms
 Iterative Learning ProcedureGradient Descent Optimizer; Evaluating Learning Processes; Minimizing a Loss Function; Minimizing the Sum of Variances; Silhouette Coefficient; LogLikelihood; Classifier Accuracy; Unsupervised Learning; kMeans Clustering; DBSCAN; Gaussian Mixtures; Supervised Learning; Naive Bayes; Linear Models; Deep Networks; Chapter 6. Hadoop MapReduce; Hadoop Distributed File System; MapReduce Architecture; Writing MapReduce Applications; Anatomy of a MapReduce Job; Hadoop Data Types; Mappers; Reducers; The Simplicity of a JSON String as Text; Deployment Wizardry
 Control code
 989872333
 Dimensions
 unknown
 Extent
 1 online resource (233 pages)
 File format
 unknown
 Form of item
 online
 Isbn
 9781491934067
 Level of compression
 unknown
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code

 c
 Other physical details
 illustrations
 http://library.link/vocab/ext/overdrive/overdriveId

 cl0500000866
 e70235cc705147ae854792180873c56a
 Quality assurance targets
 not applicable
 Reformatting quality
 unknown
 Sound
 unknown sound
 Specific material designation
 remote
 System control number
 (OCoLC)989872333
 Label
 Data science with Java : practical methods for scientists and engineers, Michael R. Brzustowicz
 Note
 Includes index
 Antecedent source
 unknown
 Carrier category
 online resource
 Carrier category code

 cr
 Carrier MARC source
 rdacarrier
 Color
 multicolored
 Content category
 text
 Content type code

 txt
 Content type MARC source
 rdacontent
 Contents

 Copyright; Table of Contents; Preface; Who Should Read This Book; Why I Wrote This Book; A Word on Data Science Today; Navigating This Book; Conventions Used in This Book; Using Code Examples; O'Reilly Safari; How to Contact Us; Acknowledgments; Chapter 1. Data I/O; What Is Data, Anyway?; Data Models; Univariate Arrays; Multivariate Arrays; Data Objects; Matrices and Vectors; JSON; Dealing with Real Data; Nulls; Blank Spaces; Parse Errors; Outliers; Managing Data Files; Understanding File Contents First; Reading from a Text File; Reading from a JSON File; Reading from an Image File
 Writing to a Text FileMastering Database Operations; CommandLine Clients; Structured Query Language; Java Database Connectivity; Visualizing Data with Plots; Creating Simple Plots; Plotting Mixed Chart Types; Saving a Plot to a File; Chapter 2. Linear Algebra; Building Vectors and Matrices; Array Storage; Block Storage; Map Storage; Accessing Elements; Working with Submatrices; Randomization; Operating on Vectors and Matrices; Scaling; Transposing; Addition and Subtraction; Length; Distances; Multiplication; Inner Product; Outer Product; Entrywise Product; Compound Operations
 Affine TransformationMapping a Function; Decomposing Matrices; Cholesky Decomposition; LU Decomposition; QR Decomposition; Singular Value Decomposition; Eigen Decomposition; Determinant; Inverse; Solving Linear Systems; Chapter 3. Statistics; The Probabilistic Origins of Data; Probability Density; Cumulative Probability; Statistical Moments; Entropy; Continuous Distributions; Discrete Distributions; Characterizing Datasets; Calculating Moments; Descriptive Statistics; Multivariate Statistics; Covariance and Correlation; Regression; Working with Large Datasets; Accumulating Statistics
 Merging StatisticsRegression; Using Builtin Database Functions; Chapter 4. Data Operations; Transforming Text Data; Extracting Tokens from a Document; Utilizing Dictionaries; Vectorizing a Document; Scaling and Regularizing Numeric Data; Scaling Columns; Scaling Rows; Matrix Scaling Operator; Reducing Data to Principal Components; Covariance Method; SVD Method; Creating Training, Validation, and Test Sets; IndexBased Resampling; ListBased Resampling; MiniBatches; Encoding Labels; A Generic Encoder; OneHot Encoding; Chapter 5. Learning and Prediction; Learning Algorithms
 Iterative Learning ProcedureGradient Descent Optimizer; Evaluating Learning Processes; Minimizing a Loss Function; Minimizing the Sum of Variances; Silhouette Coefficient; LogLikelihood; Classifier Accuracy; Unsupervised Learning; kMeans Clustering; DBSCAN; Gaussian Mixtures; Supervised Learning; Naive Bayes; Linear Models; Deep Networks; Chapter 6. Hadoop MapReduce; Hadoop Distributed File System; MapReduce Architecture; Writing MapReduce Applications; Anatomy of a MapReduce Job; Hadoop Data Types; Mappers; Reducers; The Simplicity of a JSON String as Text; Deployment Wizardry
 Control code
 989872333
 Dimensions
 unknown
 Extent
 1 online resource (233 pages)
 File format
 unknown
 Form of item
 online
 Isbn
 9781491934067
 Level of compression
 unknown
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code

 c
 Other physical details
 illustrations
 http://library.link/vocab/ext/overdrive/overdriveId

 cl0500000866
 e70235cc705147ae854792180873c56a
 Quality assurance targets
 not applicable
 Reformatting quality
 unknown
 Sound
 unknown sound
 Specific material designation
 remote
 System control number
 (OCoLC)989872333
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