The Resource Foundations of data science, Avrim Blum, Toyota Technical Institute at Chicago, John Hopcroft, Cornell University, New York, Ravindran Kannan, Microsoft Research, India
Foundations of data science, Avrim Blum, Toyota Technical Institute at Chicago, John Hopcroft, Cornell University, New York, Ravindran Kannan, Microsoft Research, India
Resource Information
The item Foundations of data science, Avrim Blum, Toyota Technical Institute at Chicago, John Hopcroft, Cornell University, New York, Ravindran Kannan, Microsoft Research, India 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 1 library branch.
Resource Information
The item Foundations of data science, Avrim Blum, Toyota Technical Institute at Chicago, John Hopcroft, Cornell University, New York, Ravindran Kannan, Microsoft Research, India 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 1 library branch.
- Summary
- "This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data"--
- Language
- eng
- Extent
- viii, 424 pages
- Contents
-
- Introduction
- High-dimensional space
- Best-fit subspaces and Singular Value Decomposition (SVD)
- Random walks and Markov chains
- Machine learning
- Algorithms for massive data problems: streaming, sketching, and sampling
- Clustering
- Random graphs
- Topic models, non-negative matrix factorization, hidden Markov models, and graphical models
- Other topics
- Wavelets
- Background material
- Isbn
- 9781108485067
- Label
- Foundations of data science
- Title
- Foundations of data science
- Statement of responsibility
- Avrim Blum, Toyota Technical Institute at Chicago, John Hopcroft, Cornell University, New York, Ravindran Kannan, Microsoft Research, India
- Language
- eng
- Summary
- "This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data"--
- Assigning source
- Provided by publisher
- Cataloging source
- DLC
- http://library.link/vocab/creatorDate
- 1966-
- http://library.link/vocab/creatorName
- Blum, Avrim
- Dewey number
- 004
- Illustrations
- illustrations
- Index
- index present
- LC call number
- QA76
- LC item number
- .B5675 2020
- Literary form
- non fiction
- Nature of contents
- bibliography
- http://library.link/vocab/relatedWorkOrContributorDate
-
- 1939-
- 1953-
- http://library.link/vocab/relatedWorkOrContributorName
-
- Hopcroft, John E.
- Kannan, Ravindran
- http://library.link/vocab/subjectName
-
- Computer science
- Statistics
- Quantitative research
- Computer science
- Quantitative research
- Statistics
- Big Data
- Data Science
- Datenanalyse
- Komplexes System
- Label
- Foundations of data science, Avrim Blum, Toyota Technical Institute at Chicago, John Hopcroft, Cornell University, New York, Ravindran Kannan, Microsoft Research, India
- Bibliography note
- Includes bibliographical references and index
- Carrier category
- volume
- Carrier category code
-
- nc
- Carrier MARC source
- rdacarrier
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
- Introduction -- High-dimensional space -- Best-fit subspaces and Singular Value Decomposition (SVD) -- Random walks and Markov chains -- Machine learning -- Algorithms for massive data problems: streaming, sketching, and sampling -- Clustering -- Random graphs -- Topic models, non-negative matrix factorization, hidden Markov models, and graphical models -- Other topics -- Wavelets -- Background material
- Control code
- 1105705800
- Dimensions
- 26 cm
- Extent
- viii, 424 pages
- Isbn
- 9781108485067
- Lccn
- 2019038133
- Media category
- unmediated
- Media MARC source
- rdamedia
- Media type code
-
- n
- System control number
- (OCoLC)1105705800
- Label
- Foundations of data science, Avrim Blum, Toyota Technical Institute at Chicago, John Hopcroft, Cornell University, New York, Ravindran Kannan, Microsoft Research, India
- Bibliography note
- Includes bibliographical references and index
- Carrier category
- volume
- Carrier category code
-
- nc
- Carrier MARC source
- rdacarrier
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
- Introduction -- High-dimensional space -- Best-fit subspaces and Singular Value Decomposition (SVD) -- Random walks and Markov chains -- Machine learning -- Algorithms for massive data problems: streaming, sketching, and sampling -- Clustering -- Random graphs -- Topic models, non-negative matrix factorization, hidden Markov models, and graphical models -- Other topics -- Wavelets -- Background material
- Control code
- 1105705800
- Dimensions
- 26 cm
- Extent
- viii, 424 pages
- Isbn
- 9781108485067
- Lccn
- 2019038133
- Media category
- unmediated
- Media MARC source
- rdamedia
- Media type code
-
- n
- System control number
- (OCoLC)1105705800
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<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.library.missouri.edu/portal/Foundations-of-data-science-Avrim-Blum-Toyota/QN5cHgNG7Xg/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.library.missouri.edu/portal/Foundations-of-data-science-Avrim-Blum-Toyota/QN5cHgNG7Xg/">Foundations of data science, Avrim Blum, Toyota Technical Institute at Chicago, John Hopcroft, Cornell University, New York, Ravindran Kannan, Microsoft Research, India</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.library.missouri.edu/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.library.missouri.edu/">University of Missouri Libraries</a></span></span></span></span></div>
