02554nam a22003257a 4500003000400000005001700004008004100021020003000062040005900092100003300151245012000184260005700304300006700361336002100428337002500449338002400474504002100498505044400519520098900963521001101952541007501963546002102038650001902059650002302078650001702101650001402118650002902132700004002161700002702201OSt20260702141618.0260702s20242024-uka|||er|||| 001 0 eng d  a9780323917780 [paperback]  aUniversity of Cebu-BaniladcUniversity of Cebu-Banilad  aKalita, Jugal K., eauthor.   aFundamentals of data science : btheory and practice / cJugal K. Kalita, Dhruba K. Bhattacharyya, and Swarup Roy.   aUnited Kingdom : bAcademic Press/Elsevier, cc2024.  axxvi, 307 pages : billustrations (black and white) ;c23 cm.   2rdacontentatext  2rdamediaaunmediated  2rdacarrieravolume   aIncludes index.   aContents: 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.  a"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   aAdult   aPurchasedxOrtega, EricyCollege of Computer StudieszComputer Science  aText in English   aData science.   aMachine learning.   aData mining.  aBig data.  aMathematical statistics.  aBhattacharyya, Dhruba K., eauthor.  aRoy, Swarup, eauthor.