Buch, Englisch, Format (B × H): 191 mm x 235 mm, Gewicht: 700 g
Theory and Practice
Buch, Englisch, Format (B × H): 191 mm x 235 mm, Gewicht: 700 g
ISBN: 978-0-323-91778-0
Verlag: William Andrew Publishing
Fundamentals of Data Science: Theory and Practice presents basic and advanced concepts in data science along with real-life applications. The book provides students, researchers and professionals at different levels a good understanding of the concepts of data science, machine learning, data mining and analytics. Users will find the authors' research experiences and achievements in data science applications, along with in-depth discussions on topics that are essential for data science projects, including pre-processing, that is carried out before applying predictive and descriptive data analysis tasks and proximity measures for numeric, categorical and mixed-type data.
The book's authors include a systematic presentation of many predictive and descriptive learning algorithms, including recent developments that have successfully handled large datasets with high accuracy. In addition, a number of descriptive learning tasks are included.
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Informatik
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizin, Gesundheitswesen Medizintechnik, Biomedizintechnik, Medizinische Werkstoffe
- Mathematik | Informatik Mathematik Mathematik Allgemein Diskrete Mathematik, Kombinatorik
- Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Biotechnologie
- Technische Wissenschaften Sonstige Technologien | Angewandte Technik Medizintechnik, Biomedizintechnik
Weitere Infos & Material
1. Introduction
2. Data, sources, and generation
3. Data preparation
4. Machine learning
5. Regression
6. Classification
7. Artificial neural networks
8. Feature selection and extraction
9. Cluster analysis
10. Ensemble learning
11. Association-rule mining
12. Big-Data analysis
13. Data Science in practice
14. Conclusion