AI is transforming networks-and networks are becoming the foundation that makes modern AI possible.Are you prepared to work confidently where these two fast-growing fields meet?AI Networking for Beginners gives you a practical, accessible foundation in both sides of this transformation: using artificial intelligence to operate smarter networks and designing high-performance infrastructure for demanding AI workloads. You do not need an advanced networking certification or machine-learning background to begin.Inside, you'll learn how to: - Understand AIOps, predictive maintenance, anomaly detection, and self-healing networks- Use observability, telemetry, and AI-driven analytics to uncover network problems faster- Explore intent-based networking, automation, Zero Trust, and intelligent threat detection- Understand why AI training and inference require specialized network architectures- Navigate leaf-spine fabrics, Clos architecture, lossless Ethernet, and GPU clusters- Compare InfiniBand, RoCE, RDMA, NVLink, and other high-performance interconnects- Recognize collective communication patterns and the causes of distributed-training bottlenecks- Build a practical learning path toward careers in AI infrastructure and network engineering- Reinforce essential terminology with a detailed glossary and acronym referenceAcross fifteen structured chapters, the book connects networking fundamentals, machine learning concepts, data center design, security, automation, and high-performance computing. Clear explanations and black-and-white conceptual illustrations help you understand not only what these technologies do, but why they matter.Whether you are a network engineer entering AI infrastructure, an IT professional preparing for changing responsibilities, or an AI practitioner seeking a stronger understanding of the systems beneath your models, this guide helps you build a connected, technically grounded view of the field.Start building the networking knowledge the AI era demands-get your copy today.
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