Andere Kunden interessierten sich auch für
![Classification and Data Science in the Digital Age]( "Classification and Data Science in the Digital Age")
Classification and Data Science in the Digital Age117,69 €![Introduction to Data Systems]( "Introduction to Data Systems")
Introduction to Data Systems53,99 €![Introduction to Data Systems]( "Introduction to Data Systems")
Introduction to Data Systems37,99 €![The Beginner's Guide to Data Science]( "The Beginner's Guide to Data Science")
The Beginner's Guide to Data Science44,99 €![Advances in Knowledge Discovery and Data Mining]( "Advances in Knowledge Discovery and Data Mining")
Advances in Knowledge Discovery and Data Mining74,99 €![Advances in Knowledge Discovery and Data Mining]( "Advances in Knowledge Discovery and Data Mining")
Advances in Knowledge Discovery and Data Mining63,99 €![The Beginner's Guide to Data Science]( "The Beginner's Guide to Data Science")
The Beginner's Guide to Data Science44,99 €
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.
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.