From Algorithms to Insights: A Review of AI Applications in Data Science

Abstract

By facilitating automation and a higher order of decision-making, AI has redefined data science. We review how the field has progressed from rule-based approaches to contemporary machine learning and deep learning, and how these have been woven into the workflow. Core tech – NLP, computer vision, reinforcement learning – now underpins predictive analytics in fields ranging from finance to cybersecurity. There are undeniable advantages, but also persistent issues around bias, privacy and interpretability. Then again, with the rise of generative and explainable AI and federated learning, we are heading for a time when data-driven systems will be more transparent and autonomous.