Introduction to data science. A Python approach to concepts, techniques and applications. 2nd edition. (English) Zbl 1543.68002
Undergraduate Topics in Computer Science. Cham: Springer (ISBN 978-3-031-48955-6/pbk; 978-3-031-48956-3/ebook). xiv, 246 p. (2024).
Publisher’s description: This accessible and classroom-tested textbook/reference 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:
See the review of the first edition in [Zbl 1365.62003].
Topics and features:
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- Provides numerous practical case studies using real-world data throughout the book
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- Supports understanding through hands-on experience of solving data science problems using Python
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- Describes concepts, techniques and tools for statistical analysis, machine learning, graph analysis, natural language processing, deep learning and responsible data science
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- Reviews a range of applications of data science, including recommender systems and sentiment analysis of text data
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- Provides supplementary code resources and data at an associated website
See the review of the first edition in [Zbl 1365.62003].
MSC:
68-01 | Introductory exposition (textbooks, tutorial papers, etc.) pertaining to computer science |
62-01 | Introductory exposition (textbooks, tutorial papers, etc.) pertaining to statistics |
62H30 | Classification and discrimination; cluster analysis (statistical aspects) |
62J05 | Linear regression; mixed models |
62J12 | Generalized linear models (logistic models) |
62R07 | Statistical aspects of big data and data science |
68T05 | Learning and adaptive systems in artificial intelligence |
68T09 | Computational aspects of data analysis and big data |
68T35 | Theory of languages and software systems (knowledge-based systems, expert systems, etc.) for artificial intelligence |
68T50 | Natural language processing |
68W10 | Parallel algorithms in computer science |
68W15 | Distributed algorithms |