Introduction to Data Science: A Python Approach to Concepts, Techniques and Applications (Undergraduate Topics in Computer Science) 2nd ed. 2024 Edition 275543
Код товару: 275543Паперова книга
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ISBN978-3031489556
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Бренд
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Автор
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Рік2024
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МоваАнглійська
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ІлюстраціїКольорові
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.
About the Author
Dr. Laura Igual is an Associate Professor at the Departament de Matematiques i Informatica, Universitat de Barcelona, Spain. Dr. Santi Segui is an Associate Professor at the same institution.
The authors wish to mention that some chapters were co-written by Jordi Vitria, Eloi Puertas, Petia Radeva, Oriol Pujol, Sergio Escalera.
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Характеристики
- Бренд
- Автор
- КатегоріяПрограмування
- Номер видання2-ге вид.
- Рік2024
- Сторінок260
- Формат155х220 мм
- ОбкладинкаМ'яка
- Тип паперуОфсетний
- МоваАнглійська
- ІлюстраціїКольорові
Від видавця
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.
About the Author
Dr. Laura Igual is an Associate Professor at the Departament de Matematiques i Informatica, Universitat de Barcelona, Spain. Dr. Santi Segui is an Associate Professor at the same institution.
The authors wish to mention that some chapters were co-written by Jordi Vitria, Eloi Puertas, Petia Radeva, Oriol Pujol, Sergio Escalera.
Introduction to Data Science: A Python Approach to Concepts, Techniques and Applications (Undergraduate Topics in Computer Science) 2nd ed. 2024 Edition
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