Expert Systems: Backward Chaining

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Related lectures (32)

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Information Extraction & Knowledge Inference

Explores information extraction, knowledge inference, taxonomy induction, and entity disambiguation.

Knowledge Representation: Introduction

Covers knowledge representation in AI, logical inference, and applications in various domains.

Knowledge Inference

Explores knowledge inference, embedding techniques, and schema matching in data integration.

Knowledge Inference: Entity Disambiguation and Graph Embeddings

Explores entity disambiguation, graph embeddings, scoring functions, and learning methods.

Inference Engines: Resolution and Horn Clauses

Covers inference engines based on resolution, Horn clauses, filtering, and unification in artificial intelligence.

Inference of Reaction Kinetics

Focuses on the inference of reaction kinetics in combustion, covering rules inference, sensitivity analysis, and Bayesian inference.

Neuro-symbolic Representations: Commonsense Knowledge & Reasoning

Explores neuro-symbolic representations for understanding commonsense knowledge and reasoning, emphasizing the challenges and limitations of deep learning in natural language processing.

Sets and Operations: Introduction to Mathematics

Covers the basics of sets and operations in mathematics, from set properties to advanced operations.

Mechanical and Biological Treatments

Explores water and waste treatment through mechanical and biological methods, focusing on composting and anaerobic digestion processes.

Bayesian Extremes: MCMC Analysis

Explores Bayesian techniques for extreme value problems, focusing on MCMC analysis and the importance of proper prior information.