Introduction to data science : a Python approach to concepts, techniques and applications /
Igual, Laura
Introduction to data science : a Python approach to concepts, techniques and applications / by Laura Igual and Santi Seguí - 2nd ed. - Cham : Springer, 2024 - xiv, 246 p. - Undergraduate topics in computer science .
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.
Eng
9783031489556 303148956X
Data mining
Artificial intelligence
Pattern Recognition
006.312 / IGU-I
Introduction to data science : a Python approach to concepts, techniques and applications / by Laura Igual and Santi Seguí - 2nd ed. - Cham : Springer, 2024 - xiv, 246 p. - Undergraduate topics in computer science .
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.
Eng
9783031489556 303148956X
Data mining
Artificial intelligence
Pattern Recognition
006.312 / IGU-I