Intelligent Data Science: A Review of AI-Based Approaches and Frameworks

Abstract

Intelligent data science is a combination of Artificial Intelligence (AI) and conventional data science, exploiting big and multicomponent data sets to uncover actionable insights. The review discusses the background knowledge, such as machine learning, deep learning, and reinforcement learning, and the ways they are used in healthcare, finance, smart cities, and IoT. The major tools and framewor66ks, like TensorFlow, PyTorch, Scikit-learn and big data platforms, are talked about in terms of scalable models development and deployment. Young issues, such as data quality, interpretability, ethical issues, and computational requirements, are examined, and new directions, such as AutoML, multi-modal learning, and real-time analytics are discussed, with an eye to the potential of AI-driven intelligent data science in the future.