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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.
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.
1. Introduction to Data Science.- 2. Toolboxes for Data Scientists.- 3. Descriptive statistics.- 4. Statistical Inference.- 5. Supervised Learning.- 6. Regression Analysis.- 7. Unsupervised Learning.- 8. Network Analysis.- 9. Recommender Systems.- 10. Statistical Natural Language Processing for Sentiment Analysis.- 11. Parallel Computing.
| Erscheinungsjahr: | 2024 |
|---|---|
| Genre: | Informatik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Seiten: | 260 |
| Reihe: | Undergraduate Topics in Computer Science |
| Inhalt: |
xiv
246 S. 4 s/w Illustr. 78 farbige Illustr. 246 p. 82 illus. 78 illus. in color. |
| ISBN-13: | 9783031489556 |
| ISBN-10: | 3031489551 |
| Sprache: | Englisch |
| Ausstattung / Beilage: | Paperback |
| Einband: | Kartoniert / Broschiert |
| Autor: |
Igual, Laura
Seguí, Santi |
| Auflage: | 2nd ed. 2024 |
| Hersteller: |
Springer International Publishing
Undergraduate Topics in Computer Science |
| Maße: | 235 x 155 x 15 mm |
| Von/Mit: | Laura Igual (u. a.) |
| Erscheinungsdatum: | 13.04.2024 |
| Gewicht: | 0,4 kg |
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.
1. Introduction to Data Science.- 2. Toolboxes for Data Scientists.- 3. Descriptive statistics.- 4. Statistical Inference.- 5. Supervised Learning.- 6. Regression Analysis.- 7. Unsupervised Learning.- 8. Network Analysis.- 9. Recommender Systems.- 10. Statistical Natural Language Processing for Sentiment Analysis.- 11. Parallel Computing.
| Erscheinungsjahr: | 2024 |
|---|---|
| Genre: | Informatik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Seiten: | 260 |
| Reihe: | Undergraduate Topics in Computer Science |
| Inhalt: |
xiv
246 S. 4 s/w Illustr. 78 farbige Illustr. 246 p. 82 illus. 78 illus. in color. |
| ISBN-13: | 9783031489556 |
| ISBN-10: | 3031489551 |
| Sprache: | Englisch |
| Ausstattung / Beilage: | Paperback |
| Einband: | Kartoniert / Broschiert |
| Autor: |
Igual, Laura
Seguí, Santi |
| Auflage: | 2nd ed. 2024 |
| Hersteller: |
Springer International Publishing
Undergraduate Topics in Computer Science |
| Maße: | 235 x 155 x 15 mm |
| Von/Mit: | Laura Igual (u. a.) |
| Erscheinungsdatum: | 13.04.2024 |
| Gewicht: | 0,4 kg |
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