AI for Data Science Authors: Zacharias Voulgaris, PhD & Yunus Emrah Bulut

AI for Data Science by Zacharias Voulgaris, PhD and Yunus Emrah Bulut is a thorough exploration of the synergy between artificial intelligence and data science. Crafted for professionals, researchers, and tech-driven problem-solvers, this book examines how AI methodologies can revolutionize the way data is analyzed, interpreted, and transformed into strategic action.

The authors demystify complex topics like machine learning, deep learning, and neural networks—breaking them down into digestible frameworks applicable across industries. With real-world case studies and robust toolkits, the book empowers readers to tackle common data challenges such as prediction modeling, anomaly detection, natural language processing, and intelligent automation.

Core highlights include:

AI tools tailored for data science workflows

Comparative analysis of ML techniques and their practical use

Deep learning architectures and training strategies

Integration of AI with big data platforms and pipelines

Ethical considerations and challenges in AI deployment

Whether you're building models from scratch or optimizing existing systems, AI for Data Science provides the clarity and tactical know-how needed to lead innovation with confidence. It’s an essential resource for anyone aiming to stay ahead in the fast-evolving world of intelligent data solutions.