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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Probabilistic Modelling for Advanced Data Analysis

Probabilistic Modelling for Advanced Data Analysis

Tyagi, Amit Kumar
Mazumdar, Soumya

Paperback

General ComputersProbability & Statistics

PREORDER - Expected ship date January 1, 2027

ISBN10: 0443452105
ISBN13: 9780443452109
Publisher: Morgan Kaufmann Publishers
Published: Jan 1 2027
Pages: 400
Weight: 0.99
Language: English
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.

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