| Management number | 238824244 | Release Date | 2026/07/11 | List Price | US$72.00 | Model Number | 238824244 | ||
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<i>Probabilistic Modelling for Advanced Data Analysis </i>provides a practical and rigorous guide for data practitioners to effectively implement probabilistic models in real-world scenarios. The book strikes a balance between high-level intuition and technical derivations, offering step-by-step explanations, real-world case studies, and Python implementation examples. The authors offer specific solutions that include modeling and quantifying uncertainty in data-driven decision-making, applying Bayesian inference to real-world problems and implementing scalable probabilistic models for large-scale datasets, all of which contribute to explainable and trustworthy AI. <p>This book presents readers with theoretical foundations and practical applications of probabilistic modeling, providing a structured approach for researchers, data scientists, and industry professionals. It meets the increasing demand for uncertainty-aware AI models, Bayesian inference, and probabilistic graphical models across various fields of research.</p>
| Book format | Paperback |
|---|---|
| Fiction/nonfiction | Non-Fiction |
| Genre | Computing & Internet |
| Publication date | January, 2027 |
| Pages | 400 |
| Subgenre | Data Science |
| Series title | No Series |
| Number in series | 0 |
| Edition | 1 |
| Publisher | Elsevier Science |
| Language | English |
| Is collectible | N |
| Recording time | 0 min |
| Retail packaging | Single Piece |
| Assembled product dimensions (l x w x h) | 7.50 x 6.00 x 9.25 in |
| Assembled product weight | 0.99 lb |
| Bisac subject heading | Computers |
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