Probabilistic Modelling for Advanced Data Analysis

By Amit Kumar Tyagi PhD.

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.

• Format: Paperback
• Language: English
• ISBN: 0443452105
• ISBN13: 9780443452109
• Release Date: January 2027
• Publisher: Morgan Kaufmann Publishers
• Length: 400 Pages
• Weight: 0.99 lbs.