نبذة تعريفية / مختصر السيرة الذاتية
Khalil El Hindi is a professor in the Department of Computer Science at King Saud University. His research focuses on: Machine Learning (classifier ensembles, instance weighting), Deep Learning (architectures like CNNs, RNNs, and transformers), Nature-Inspired Optimization Algorithms (genetic algorithms, swarm intelligence), Outlier Detection and anomaly analysis, Similarity/Distance Metrics for data analysis.
المنشورات
المزيد ...
The combination of collaborative deep learning and Cyber-Physical Systems (CPSs) has the potential to improve decision-making, adaptability, and efficiency in dynamic and distributed environments…
Naïve Bayes (NB) classification performance degrades if the conditional independence assumption is not satisfied or if the conditional probability estimate is not realistic due to the attributes…
المواد الدراسية
المزيد ...
This course gives an overview of machine learning concepts, techniques, and algorithms. Topics include Linear Regression, Logistic Regression, Support Vector Machine, Decision Tree Learning, k-…
The course provides an introduction to artificial intelligence. Topics include problem-solving using search (uninformed search, informed search, local search, constraint satisfaction…