Linkedin Learning – Introduction to Probabilistic Knowledge Graphs: AI-Driven Inference and Real-World Applications 2026
English | Tutorial | Size: 708.86 MB
Probabilistic knowledge graphs (PKGs) are transforming the way data is structured and analyzed in AI and machine learning. In this course, AI engineer and author Vaibhava Lakshmi Ravideshik introduces the fundamentals of knowledge graphs and shows how probability theory helps manage uncertainty in data. Through hands-on examples, learn how to construct PKGs, integrate probabilistic reasoning, and apply inference techniques like Markov Chain Monte Carlo (MCMC). Explore real-world applications in decision-making, risk assessment, and predictive modeling, and gain insights into scaling challenges and emerging trends shaping the future of PKGs.
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