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Probabilistic Modelling for Advanced Data Analysis Amit Kumar PhD. Tyagi
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Probabilistic Modelling for Advanced Data Analysis
Amit Kumar PhD. Tyagi
Probabilistic Modelling for Advanced Data Analysis 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.
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.
| Media | Books Paperback Book (Book with soft cover and glued back) |
| To be released | 2027 |
| ISBN13 | 9780443452109 |
| Publishers | Elsevier Science & Technology |
| Pages | 400 |
| Dimensions | 150 × 220 × 10 mm · 450 g |
