Data Science and Predictive Analytics by Ivo D Dinov
This textbook integrates important mathematical foundations, efficient computational algorithms, applied statistical inference techniques, and cutting-edge machine learning approaches to address a wide range of crucial biomedical informatics, health analytics applications, and decision science challenges.
Professor Ivo D. Dinov directs the Statistics Online Computational Resource (SOCR) at the University of Michigan and serves as associate director of the Michigan Institute for Data Science (MIDAS). He is an expert in mathematical modeling, statistical analysis, high-throughput computational processing, and scientific visualization of large, complex and heterogeneous datasets (Big Data). Dr. Dinov is developing, validating, and disseminating novel technology-enhanced pedagogical approaches for STEM education and active data science learning. His artificial intelligence and machine learning work involves compressive big data analytics, statistical obfuscation of sensitive data, complex time (kime) representation, model-based and model-free techniques for kimesurface analytics. Dr. Dinov is a member of the American Statistical Association, the American Mathematical Society, the American Physical Society, the American Association for the Advancement of Science, an honorary member ofthe Sigma Theta Tau International Society, and an elected member of the International Statistical Institute.
| SKU | Unavailable |
| ISBN 13 | 9783031174827 |
| ISBN 10 | 3031174828 |
| Title | Data Science and Predictive Analytics |
| Author | Ivo D Dinov |
| Series | The Springer Series In Applied Machine Learning |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Springer International Publishing AG |
| Year published | 2023-02-17 |
| Number of pages | 918 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |