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Introduction to Data Science

A Python Approach to Concepts, Techniques and Applications

Produktform: E-Buch Text Elektronisches Buch in proprietärem

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: 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 scienceReviews 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.weiterlesen

Dieser Artikel gehört zu den folgenden Serien

Elektronisches Format: PDF

Sprache(n): Englisch

ISBN: 978-3-031-48956-3 / 978-3031489563 / 9783031489563

Verlag: Springer International Publishing

Erscheinungsdatum: 12.04.2024

Seiten: 246

Auflage: 2

Beiträge von Jordi Vitrià, Sergio Escalera, Oriol Pujol, Petia Radeva, Eloi Puertas, Francesc Dantí, Lluís Garrido
Autor(en): Laura Igual, Santi Seguí

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