This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the emerging and interdisciplinary field of data science. The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing 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 techniques and tools for statistical analysis, machine learning, graph analysis, and parallel programming
• 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 Assistant Professor at the same institution.

Autorentext

Dr. Laura Igual is an Associate Professor at the Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Spain. Dr. Santi Seguí is an Assistant 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, Francesc Dantí and Lluís Garrido.

Inhalt

Introduction to Data Science Jordi Vitrià

Toolboxes for Data Scientists Eloi Puertas and Francesc Dantí

Descriptive statistics Petia Radeva and Laura Igual

Statistical Inference Jordi Vitrià and Sergio Escalera

Supervised Learning Oriol Pujol and Petia Radeva

Regression Analysis Laura Igual and Jordi Vitrià

Unsupervised Learning Petia Radeva and Oriol Pujol

Network Analysis Laura Igual and Santi Seguí

Recommender Systems Santi Seguí and Eloi Puertas

Statistical Natural Language Processing for Sentiment Analysis Sergio Escalera and Santi Seguí

Parallel Computing Francesc Dantí and Lluís Garrido