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Probabilistic Modelling for Advanced Data Analysis

Häftad, Engelska, 2027

AvAmit Kumar Tyagi,Soumya Mazumdar

2 299 kr

Kommande

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.

  • Includes real-world case studies from various industries and step-by-step Python implementations of probabilistic models
  • Presents visual explanations, graphical representations, easy-to-follow analogies, and a focus on Bayesian methods, uncertainty quantification, and probabilistic inference
  • Features approximate inference techniques, probabilistic deep learning approaches for AI applications, and strategies for handling high-dimensional data with probabilistic models

Produktinformation

  • Utgivningsdatum2027-01-01
  • Mått191 x 235 x undefined mm
  • Vikt450 g
  • FormatHäftad
  • SpråkEngelska
  • Antal sidor400
  • FörlagElsevier Science
  • ISBN9780443452109

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