Verwandte Artikel zu Introduction to Data Science: A Python Approach to...
Introduction to Data Science: A Python Approach to Concepts, Techniques and Applications (Undergraduate Topics in Computer Science) - Softcover
Inhaltsangabe
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.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Über die Autorin bzw. den Autor
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.
Von der hinteren Coverseite
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
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.
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.
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
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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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Introduction to Data Science
Verlag:
Springer International Publishing, 2024
ISBN 10: 3031489551
ISBN 13: 9783031489556
Neu
Softcover
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Zustand: New. Describes tools and techniques that demystify data scienceDiscusses Python extensions, techniques and modules to perform statistical analysis and machine learningIncludes case studies, and supplies code examples and data at an associated we. Artikel-Nr. 1276622158
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Introduction to Data Science
ISBN 10: 3031489551
ISBN 13: 9783031489556
Neu
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Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. Neuware -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 bookSupports understanding through hands-on experience of solving data science problems using PythonDescribes 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 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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 260 pp. Englisch. Artikel-Nr. 9783031489556
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Introduction to Data Science : A Python Approach to Concepts, Techniques and Applications
Verlag:
Springer International Publishing, 2024
ISBN 10: 3031489551
ISBN 13: 9783031489556
Neu
Taschenbuch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: 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. Artikel-Nr. 9783031489556
Anzahl: 1 verfügbar
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Introduction to Data Science
Verlag:
Springer International Publishing AG, 2024
ISBN 10: 3031489551
ISBN 13: 9783031489556
Neu
PAP
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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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Introduction to Data Science: A Python Approach to Concepts, Techniques and Applications
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