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Introduction to Data Science: A Python Approach to Concepts, Techniques and Applications - Couverture souple
Synopsis
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 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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
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.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Introduction to Data Science: A Python Approach to Concepts, Techniques and Applications (Undergraduate Topics in Computer Science)
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Springer, 2024
ISBN 10 : 3031489551
ISBN 13 : 9783031489556
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INTRODUCTION TO DATA SCIENCE : A PYTHON
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Introduction to Data Science
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Springer International Publishing AG, 2024
ISBN 10 : 3031489551
ISBN 13 : 9783031489556
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Introduction to Data Science
Edité par
Springer International Publishing AG, 2024
ISBN 10 : 3031489551
ISBN 13 : 9783031489556
Neuf
PAP
Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni
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Introduction to Data Science
Edité par
Springer International Publishing AG, CH, 2024
ISBN 10 : 3031489551
ISBN 13 : 9783031489556
Neuf
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Vendeur : Rarewaves.com UK, London, Royaume-Uni
Évaluation du vendeur 4 sur 5 étoiles
Paperback. Etat : New. 2nd ed. 2024. 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. N° de réf. du vendeur LU-9783031489556
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Edité par
Springer International Publishing, 2024
ISBN 10 : 3031489551
ISBN 13 : 9783031489556
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Introduction to Data Science
Edité par
Springer International Publishing AG, CH, 2024
ISBN 10 : 3031489551
ISBN 13 : 9783031489556
Neuf
Paperback
Vendeur : Rarewaves.com USA, London, LONDO, Royaume-Uni
Évaluation du vendeur 4 sur 5 étoiles
Paperback. Etat : New. 2nd ed. 2024. 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. N° de réf. du vendeur LU-9783031489556
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ISBN 10 : 3031489551
ISBN 13 : 9783031489556
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Introduction to Data Science : A Python Approach to Concepts, Techniques and Applications
Edité par
Springer International Publishing, 2024
ISBN 10 : 3031489551
ISBN 13 : 9783031489556
Neuf
Taschenbuch
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the interdisciplinary field of data science. The coverage spans key conceptsfrom statistics, machine/deeplearningand responsible data science,useful techniques fornetworkanalysis andnatural language processing,and practical applicationsof data science such as recommender systems or sentiment analysis.Topics and features:Provides numerous practical case studies using real-world data throughout the bookSupports understanding through hands-on experience of solving data science problems using PythonDescribesconcepts,techniques and tools for statistical analysis, machine learning, graph analysis,natural language processing, deep learning andresponsible data scienceReviews a range of applications of data science, including recommender systems and sentiment analysis of text dataProvides supplementary code resources and data at an associated websiteThis 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. N° de réf. du vendeur 9783031489556
Quantité disponible : 1 disponible(s)