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.
| ISBN: | 9783319500164 |
| Publication date: | 2nd March 2017 |
| Author: | Laura Igual, Santi Seguí, Jordi Vitrià, Eloi Puertas |
| Publisher: | Springer International Publishing AG |
| Format: | Paperback |
| Pagination: | 218 pages |
| Series: | Undergraduate Topics in Computer Science |
| Genres: |
Data mining Expert systems / knowledge-based systems Maths for computer scientists Probability and statistics Artificial intelligence Pattern recognition Mathematical and statistical software |