Advanced Machine Learning Techniques for Intelligent Information Technology Systems

Abstract

Advanced Machine Learning (ML) techniques are transforming Intelligent Information Technology (IT) systems by enabling automated decision-making, predictive analytics, and adaptive optimization. These techniques, including deep learning, reinforcement learning, ensemble learning, and transfer learning, allow IT systems to process large-scale heterogeneous datasets, extract patterns, and provide actionable insights in real time. This review explores the application of advanced ML methods in enhancing IT infrastructure performance, security, resource allocation, and decision support. Challenges related to data quality, computational complexity, model interpretability, and integration with existing IT frameworks are discussed. Future directions emphasize scalable, energy-efficient, and explainable ML solutions for intelligent IT systems. [1–5]