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Mastering AI SDKs: A Practical Guide to Building Production-Ready Applications with Leading LLM Platforms

by Fred Thompson
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Book cover type: Paperback
  • ISBN13: 9798261862888
  • Binding: Paperback
  • Subject: N/A
  • Publisher: Independently Published
  • Publisher Imprint: Independently Published
  • Publication Date:
  • Pages: 120
  • Original Price: USD 17.99
  • Language: English
  • Edition: N/A
  • Item Weight: 150 grams
  • BISAC Subject(s): Artificial Intelligence / Generative AI

Unlock the full power of artificial intelligence development and elevate your skills from novice to expert with the most comprehensive guide to AI SDKs ever published. Mastering AI SDKs: A Practical Guide to Building Production-Ready Applications with Leading LLM Platforms is the definitive all-in-one resource for harnessing the capabilities of large language models (LLMs) in real-world software. Whether you're new to AI integration or an experienced developer seeking to optimize and scale your applications, this book will lead you step by step from core concepts to sophisticated, enterprise-level implementations.

Inside, you'll discover how to:

  • Grasp the fundamentals of LLMs and AI SDKs, including key terminology, model comparisons, and best practices for setup.
  • Configure robust development environments with tools, dependencies, and secure authentication across platforms.
  • Dive deep into leading SDKs from OpenAI, Google Vertex AI, Anthropic, xAI, Meta, Mistral, Cohere, and DeepSeek.
  • Master advanced techniques like prompt engineering, fine-tuning, retrieval-augmented generation (RAG), and agentic workflows.
  • Deploy, scale, secure, and ethically govern AI applications in production, with monitoring, cost optimization, and compliance strategies.
  • Explore real-world case studies, hands-on exercises, and a bonus kit of code templates, datasets, and evaluation tools you can adapt immediately.

Unlike fragmented tutorials or superficial overviews, this book delivers a complete mastery path-blending authoritative expertise, practical projects, and insights from industry leaders in AI engineering. By the end, you won't just "experiment" with LLMs; you'll command them as a strategic asset for innovation, efficiency, and competitive advantage.

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