📘 Handbook of Probabilistic Models PDF
Edited by Pijush Samui, Deyu Tian Bui, Subrata Chakraborty & Ravinesh C. Deo
Advanced probabilistic modeling for modern scientific and data-driven applications
✔ Probabilistic Modeling | ✔ Advanced Research | ✔ Instant PDF Download
Comprehensive coverage of modern probabilistic techniques.
Download and reference immediately.
Quickly locate models, algorithms, and applications.
About This Book
Handbook of Probabilistic Models is a comprehensive reference that brings together modern probabilistic modeling approaches used across engineering, data science, artificial intelligence, and applied sciences.
Published by Butterworth-Heinemann (Elsevier), the handbook presents both theoretical foundations and practical implementations, making it suitable for advanced academic study and applied research.
What You Will Gain from This Book
- 🧠 Deep understanding of probabilistic modeling frameworks
- 📊 Methods for uncertainty quantification and inference
- 🤖 Applications in machine learning and AI
- 📈 Tools for modeling complex stochastic systems
- 🎯 Support for advanced research and development
Key Topics Covered
- ✔ Probability distributions and stochastic processes
- ✔ Bayesian inference and probabilistic reasoning
- ✔ Uncertainty modeling and risk assessment
- ✔ Machine learning and probabilistic algorithms
- ✔ Engineering and scientific applications
Why the PDF Edition Is Ideal
- 💻 Access on laptop, tablet, or workstation
- 🖍 Annotate models, equations, and research notes
- 🔍 Search concepts, symbols, and methodologies instantly
- ⚡ Ideal for research, coursework, and technical reference
Who This Book Is For
- Researchers in probability, statistics, and data science
- Graduate and postgraduate students
- Engineers and scientists modeling uncertainty
- AI and machine learning practitioners
Frequently Asked Questions
Is this an advanced-level book?
Yes. It is intended for advanced academic and professional audiences.
Does it include machine learning applications?
Yes. Many chapters apply probabilistic models to ML and AI problems.
Is this suitable for research use?
Yes. It is designed as a comprehensive research reference.
How do I receive the PDF?
Instant download access is provided after purchase.
