Introduction to data science : a Python approach to concepts, techniques and applications / by Laura Igual and Santi Seguí

By:

Igual, Laura

Contributor(s):

Santi Segui

Material type:

TextSeries: Undergraduate topics in computer sciencePublication details: Cham : Springer, 2024Edition: 2nd edDescription: xiv, 246 pISBN:

9783031489556
303148956X

Subject(s):

DDC classification:

006.312 IGU-I

Summary: 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.

Item type:

Books

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Current library	Call number	Status	Barcode
UMT Main Campus	006.312 IGU-I (Browse shelf(Opens below))	Available	152246

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Includes bibliographical references and index

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.

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