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Data Engineering for AI/ML Pipelines: A Comprehensive Guide to Building Scalable, Intelligent Data Workflows

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Description

Data Engineering for AI/ML Pipelines: Build Scalable, Intelligent Workflows. The definitive guide to mastering data engineering for AI and machine learning pipelines,updated with the latest tools, real-world case studies, and proven strategies. Whether you're a data engineer, ML practitioner, or tech leader, this comprehensive book equips you to design high-performance, production-ready AI/ML pipelines that scale from prototype to enterprise. In today’s AI-driven world, data is the new oil, but only if refined through robust, intelligent pipelines. Data Engineering for AI/ML Pipelines takes you beyond theory into actionable practice, covering every stage of the modern data lifecycle with real code, and benchmarks. Why this book stands out: 12 in-depth chapters with Python code examples, PySpark workflows, and Airflow 2.10+ DAGs Up-to-date 2025 tools: Apache Kafka 3.8, Flink 2.0, dbt Core 1.9, Databricks Unity Catalog, Snowflake Cortex, Feast, and emerging AI platforms Real-world case studies from healthcare, finance, and robotics, featuring Physical AI, RAG pipelines, and real-time analytics What you’ll master: Ingest and process structured, unstructured, and streaming data at scale Automate data cleansing, feature engineering, and anomaly detection with AI Orchestrate ML workflows using Kubeflow, Prefect, and Airflow Secure pipelines with differential privacy, federated learning, and zero-trust models Optimize cost and performance with mathematical models and simulations Future-proof with edge AI, quantum-ready data models, and interoperability protocols (MCP, A2A) Includes: GitHub-ready code repos and public datasets Appendix with tool benchmarks, glossaries, and resources “The backbone of every successful AI system is a bulletproof data pipeline. This book is your blueprint.” – Dr. Alex J. Sterling Don’t let poor data engineering derail your AI initiatives. Grab your copy today and build scalable, intelligent, future-ready ML pipelines that deliver real business impact.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
13 November 2025
Listed Since
13 November 2025

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