Data Science & AI Books

Differential Privacy in Artificial Intelligence: From Theory to Practice is a comprehensive resource designed to review the principles and applications of differential privacy in a world increasingly driven by data. This book delves into the theoretical underpinnings of differential privacy, its use in machine learning systems, practical implementa

Compressed sensing, also known as sparse representation or sparse modeling, has experienced substantial growth in research fields such as signal processing, machine learning, and statistics. In recent years, this powerful tool has been successfully applied to the design of control systems. This book provides a comprehensive guide to compressed sens

As generative artificial intelligence (AI) rapidly transforms legal practice, the profession faces opportunities and challenges in adopting these technologies. GenAI for Legal Practice provides a comprehensive and accessible guide to integrating generative AI tools into Australian legal practice, offering both theoretical foundations and practical

Artificial intelligence (AI) depends on data. In sensitive domains - such as healthcare, security, finance, and many more - there is therefore tension between unleashing the power of AI and maintaining the confidentiality and security of the relevant data. This book - intended for researchers in academia and R&D engineers in industry - explains how

Information theory deals with mathematical laws that govern the flow, representation and transmission of information, just as the field of physics concerns laws that govern the behavior of the physical universe. The foundation was made in the context of communication while characterizing the fundamental limits of communication and offering codes (s

Enterprises in traditional and emerging industries alike are increasingly turning to machine learning (ML) to maximize the value of their business data. But many of these teams are likely to experience significant hurdles and setbacks throughout the journey. In this practical ebook, data scientists and machine learning engineers explore six common

The data-driven revolution is finally hitting the media and entertainment industry. For decades, broadcast television and print media relied on traditional delivery channels for solvency and growth, but those channels fragmented as cable, streaming, and digital devices stole the show. In this ebook, you'll learn about the trends, challenges, and op

This book originated from lecture notes developed by the lead author for a course in applied numerical methods, initially designed for Civil Engineering majors, and later expanded to include Mechanical Engineering. The primary objectives of the text are to introduce the fundamental concepts of numerical methods and to provide a thorough, integrated

IBM Synthetic Data Sets is a family of artificially generated, enterprise-grade datasets that enhance predictive artificial intelligence (AI) model training and large language models (LLMs) to benefit IBM Z and IBM LinuxONE clients, ecosystems, and independent software vendors. These pre-built datasets are downloadable and packaged as comma-separat

The AI Toolkit for IBM Z and LinuxONE is a comprehensive suite of tools designed to streamline the development and deployment of AI models on IBM's enterprise-grade platforms. This toolkit empowers developers and data scientists to leverage the power of IBM Z and LinuxONE systems for AI workloads, offering a seamless integration with popular AI fra