theory and practice Kalita, Jugal K. creator author. Bhattacharyya, Dhruba K. author. Roy, Swarup author. text -uk United Kingdom Academic Press/Elsevier c2024 2024 monographic eng xxvi, 307 pages : illustrations (black and white) ; 23 cm. "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." --Provided by the publisher Contents: Preface — Acknowledgement — Foreword — Foreword — 1. Introduction — 2. Data, sources, and generation — 3. Data preparation — 4. Machine learning — 5. Regression — 6. Classification — 7. Artificial neural networks — 8. Feature selection — 9. Cluster analysis — 10. Ensemble learning — 11. Association-rule mining — 12. Big data analysis — 13. Data science in practice — 14. Conclusion — Index. Adult adult Jugal K. Kalita, Dhruba K. Bhattacharyya, and Swarup Roy. Includes index. Purchased Ortega, Eric College of Computer Studies Computer Science Text in English Data science Machine learning Data mining Big data Mathematical statistics 9780323917780 [paperback] University of Cebu-Banilad 260702 20260702141618.0