Probabilistic Modelling for Advanced Data Analysis
local_shippingShip to Me
Overview
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.
This item is Non-Returnable
Customers Also Bought
Details
- ISBN-13: 9780443452109
- ISBN-10: 0443452105
- Publisher: Morgan Kaufmann Publishers
- Publish Date: January 2027
- Shipping Weight: 0.99 pounds
- Page Count: 400
Related Categories
