This hands-on guide offers clear explanations of fuzzy logic along with practical applications and real-world examples. Written by an award-winning engineer, “Fuzzy Logic: Applications in Artificial ...

Inductive logic programming (ILP) and machine learning together represent a powerful synthesis of symbolic reasoning and statistical inference. ILP focuses on deriving interpretable logic rules from ...

The field of interpretability investigates what machine learning (ML) models are learning from training datasets, the causes and effects of changes within a model, and the justifications behind its ...

The intersection of machine learning and mathematical logic — spanning computer science, pure mathematics, and statistics — has catalyzed recent advances in artificial intelligence and deep learning ...

AI, Machine Learning & Robotics research at Drexel University's College of Computing & Informatics (CCI) explores algorithms, mathematics, and applications of artificial intelligence (AI) through ...

Gain a deeper understanding of artificial intelligence with Machine Learning Fundamentals: Principles and Applications. This course explores core concepts and practical uses of supervised and ...

Large language models have captured the news cycle, but there are many other kinds of machine learning and deep learning with many different use cases. Amid all the hype and hysteria about ChatGPT, ...

Systems controlled by next-generation computing algorithms could give rise to better and more efficient machine learning products, a new study suggests. Systems controlled by next-generation computing ...

Artificial intelligence (AI) is no longer a buzzword; it has become an integral part of our lives, influencing every aspect of society in ways we could only dream of just a few years ago. AI has made ...

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. Intelligent organizations prioritize investments in machine learning and real-time data to ...