| Document Type
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BL
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| Record Number
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809986
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| Doc. No
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GBB8O1644b624002
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| Main Entry
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Igual, Laura.
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| Title & Author
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Introduction to data science : : a Python approach to concepts, techniques and applications /\ Laura Igual, Santi Seguí ; with contributions from Jordi Vitrià [and others].
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| Publication Statement
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Cham, Switzerland :: Springer,, 2017.
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| Series Statement
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Undergraduate topics in computer science,
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| Page. NO
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1 online resource
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| ISBN
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9783319500171
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: 3319500171
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9783319500164
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3319500163
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| Bibliographies/Indexes
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Includes bibliographical references and index.
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| Contents
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Introduction to Data Science -- Toolboxes for Data Scientists -- Descriptive statistics -- Statistical Inference -- Supervised Learning -- Regression Analysis -- Unsupervised Learning -- Network Analysis -- Recommender Systems -- Statistical Natural Language Processing for Sentiment Analysis -- Parallel Computing.
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| Abstract
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This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the emerging and interdisciplinary field of data science. The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentiment analysis. Topics and features: Provides numerous practical case studies using real-world data throughout the book Supports understanding through hands-on experience of solving data science problems using Python Describes techniques and tools for statistical analysis, machine learning, graph analysis, and parallel programming Reviews a range of applications of data science, including recommender systems and sentiment analysis of text data Provides supplementary code resources and data at an associated website<This practically-focused textbook provides an ideal introduction to the field for upper-tier undergraduate and beginning graduate students from computer science, mathematics, statistics, and other technical disciplines. The work is also eminently suitable for professionals on continuous education short courses, and to researchers following self-study courses. Dr. Laura Igual is an Associate Professor at the Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Spain. Dr. Santi Seguí is an Assistant Professor at the same institution.
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| Subject
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Quantitative research.
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| Subject
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Python (Computer program language)
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Maths for computer scientists.
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Artificial intelligence.
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Pattern recognition.
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Mathematical statistical software.
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| Subject
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Data mining.
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| Subject
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Computers-- Mathematical Statistical Software.
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Computers-- Intelligence (AI) Semantics.
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Computers-- Computer Vision Pattern Recognition.
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Computers-- Database Management-- Data Mining.
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| Subject
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Python (Computer program language)
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| Subject
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Quantitative research.
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| Dewey Classification
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001.4/2
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| LC Classification
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Q180.55.Q36
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| Added Entry
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Seguí, Santi.
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