Introduction to Data Science (Record no. 87834)

000 -LEADER
fixed length control field 04131nam a22005655i 4500
001 - CONTROL NUMBER
control field 978-3-031-48956-3
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240730171824.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 240412s2024 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783031489563
-- 978-3-031-48956-3
082 04 - CLASSIFICATION NUMBER
Call Number 005.7
100 1# - AUTHOR NAME
Author Igual, Laura.
245 10 - TITLE STATEMENT
Title Introduction to Data Science
Sub Title A Python Approach to Concepts, Techniques and Applications /
250 ## - EDITION STATEMENT
Edition statement 2nd ed. 2024.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XIV, 246 p. 82 illus., 78 illus. in color.
490 1# - SERIES STATEMENT
Series statement Undergraduate Topics in Computer Science,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 1. Introduction to Data Science -- 2. Toolboxes for Data Scientists -- 3. Descriptive statistics -- 4. Statistical Inference -- 5. Supervised Learning -- 6. Regression Analysis -- 7. Unsupervised Learning -- 8. Network Analysis -- 9. Recommender Systems -- 10. Statistical Natural Language Processing for Sentiment Analysis -- 11. Parallel Computing.
520 ## - SUMMARY, ETC.
Summary, etc This textbook presents an introduction to the fundamentals of the interdisciplinary field of data science. The coverage spans key concepts from statistics, machine/deep learning and responsible data science, useful techniques for network analysis and natural language processing, and practical applications of data science such as recommender systems or 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 concepts, techniques and tools for statistical analysis, machine learning, graph analysis, natural language processing, deep learning and responsible data science 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 Associate Professor at the same institution. The authors wish to mention that some chapters were co-written by Jordi Vitrià, Eloi Puertas, Petia Radeva, Oriol Pujol, Sergio Escalera.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
General subdivision Data processing.
700 1# - AUTHOR 2
Author 2 Seguí, Santi.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-031-48956-3
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
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-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2024.
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-- text
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-- computer
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-- rdamedia
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-- online resource
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-- text file
-- PDF
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650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Data mining.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Python (Computer program language).
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial intelligence.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Data Science.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Data Mining and Knowledge Discovery.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Python.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Artificial Intelligence.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 2197-1781
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