Machine Learning and Symbolic Reasoning - Integrating AI Technologies
Offered By: Devoxx via YouTube
Course Description
Overview
Explore the integration of Machine Learning and Symbolic Reasoning in AI applications through this insightful conference talk by Nicole Prentzas and Mario Fusco. Discover how combining these complementary AI branches can lead to more transparent and explainable decision-making processes. Learn about the limitations of relying solely on Machine Learning and the benefits of incorporating Symbolic Artificial Intelligence for encoding domain-specific knowledge. Gain practical insights into implementing this hybrid approach using Quarkus with its langchain4j and drools extensions. Understand the importance of explainable AI in critical applications, such as mortgage approvals, where transparency is crucial. Benefit from the expertise of Nicole Prentzas, a senior software engineer and PhD candidate in Explainable AI, and Mario Fusco, a senior principal software engineer and Drools project lead. Delve into real-world examples demonstrating the advantages of this architectural choice in common scenarios.
Syllabus
[VDTRIESTE24] Machine Learning + Symbolic Reasoning - Conference by Nicole Prentzas and Mario Fusco
Taught by
Devoxx
Related Courses
Explainable AI: Scene Classification and GradCam VisualizationCoursera Project Network via Coursera Artificial Intelligence Privacy and Convenience
LearnQuest via Coursera Natural Language Processing and Capstone Assignment
University of California, Irvine via Coursera Modern Artificial Intelligence Masterclass: Build 6 Projects
Udemy Data Science for Business
DataCamp