Data Engineering for AI/ML Pipelines: Ultimate guide to data pipelines and architectures for AI/ML applications (English Edition)

Comprehensive guide to building scalable AI/ML data engineering pipelines. Practical insights into data collection, storage, processing, and analysis. Emphasis on data security, privacy, and emerging trends in AI/ML. Data engineering is the art of building and managing data pipelines that enable efficient data flow for AI/ML projects. This book serves as a comprehensive guide to data engineering for AI/ML systems, equipping you with the knowledge and skills to create robust and scalable data infrastructure. This book covers everything from foundational concepts to advanced techniques. It begins by introducing the role of data engineering in AI/ML, followed by exploring the lifecycle of data, from data generation and collection to storage and management. Readers will learn how to design robust data pipelines, transform data, and deploy AI/ML models effectively for real-world applications. The book also explains security, privacy, and compliance, ensuring responsible data management. Finally, it explores future trends, including automation, real-time data processing, and advanced architectures, providing a forward-looking perspective on the evolution of data engineering.

• | Author: Mitesh Mangaonkar, Venkata Karthik Penikalapati
• | Publisher: De Gruyter
• | Publication Date: Nov 01, 2024
• | Number of Pages:
• | Language: eng
• | Binding: Digital (delivered electronically)
• | ISBN-13: 9789365899030
• | ISBN-10: 9365899036