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Intelligent Systems Engineering: Empowering the Node.js Backend with Natural Language Processing with LLM (The Full-Stack AI Systems Series, Band 4) - Softcover
Buch 2 von 2: The Full-Stack AI Systems Series
Inhaltsangabe
Your Node.js backend can do far more than send requests to an LLM. It can become the foundation of a scalable, secure, intelligent AI application.
Intelligent Systems Engineering explores how Node.js developers can move beyond basic API integrations and engineer production-ready applications powered by large language models and modern natural language processing.
From connecting multiple LLM providers to building RAG pipelines, managing conversational memory, orchestrating AI agents, and controlling inference costs, this book focuses on the engineering decisions that matter when AI applications move from prototype to production.
Inside, you’ll explore:
- OpenAI, Anthropic, and Google AI integrations with Node.js
- Prompt engineering, structured outputs, and prompt-injection defenses
- RAG pipelines, embeddings, vector databases, and semantic search
- Redis-powered conversational memory and context management
- Agentic workflows, function calling, MCP, and human-in-the-loop patterns
- Semantic caching, batching, rate limiting, and token-cost optimization
- PII protection, audit logging, privacy, and enterprise AI security
- LLM testing, hallucination mitigation, RAG evaluation, and prompt benchmarking
- High-concurrency architectures using WebSockets, SSE, containers, and serverless deployments
Build smarter backends. Engineer more reliable LLM applications.
Bring intelligent systems to life with Node.js.
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Intelligent Systems Engineering
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Paperback. Zustand: new. Paperback. Your Node.js backend can do far more than send requests to an LLM. It can become the foundation of a scalable, secure, intelligent AI application.Intelligent Systems Engineering explores how Node.js developers can move beyond basic API integrations and engineer production-ready applications powered by large language models and modern natural language processing.From connecting multiple LLM providers to building RAG pipelines, managing conversational memory, orchestrating AI agents, and controlling inference costs, this book focuses on the engineering decisions that matter when AI applications move from prototype to production.Inside, you'll explore: OpenAI, Anthropic, and Google AI integrations with Node.jsPrompt engineering, structured outputs, and prompt-injection defensesRAG pipelines, embeddings, vector databases, and semantic searchRedis-powered conversational memory and context managementAgentic workflows, function calling, MCP, and human-in-the-loop patternsSemantic caching, batching, rate limiting, and token-cost optimizationPII protection, audit logging, privacy, and enterprise AI securityLLM testing, hallucination mitigation, RAG evaluation, and prompt benchmarkingHigh-concurrency architectures using WebSockets, SSE, containers, and serverless deploymentsWhether you're a Node.js developer entering AI engineering or an engineer building production LLM applications, this guide connects JavaScript backend development with the practical realities of modern generative AI. Build smarter backends. Engineer more reliable LLM applications.Bring intelligent systems to life with Node.js. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9798172784033
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Intelligent Systems Engineering: Empowering the Node.js Backend with Natural Language Processing with LLM (The Full-Stack AI Systems Series)
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Paperback. Zustand: new. Paperback. Your Node.js backend can do far more than send requests to an LLM. It can become the foundation of a scalable, secure, intelligent AI application.Intelligent Systems Engineering explores how Node.js developers can move beyond basic API integrations and engineer production-ready applications powered by large language models and modern natural language processing.From connecting multiple LLM providers to building RAG pipelines, managing conversational memory, orchestrating AI agents, and controlling inference costs, this book focuses on the engineering decisions that matter when AI applications move from prototype to production.Inside, you'll explore: OpenAI, Anthropic, and Google AI integrations with Node.jsPrompt engineering, structured outputs, and prompt-injection defensesRAG pipelines, embeddings, vector databases, and semantic searchRedis-powered conversational memory and context managementAgentic workflows, function calling, MCP, and human-in-the-loop patternsSemantic caching, batching, rate limiting, and token-cost optimizationPII protection, audit logging, privacy, and enterprise AI securityLLM testing, hallucination mitigation, RAG evaluation, and prompt benchmarkingHigh-concurrency architectures using WebSockets, SSE, containers, and serverless deploymentsWhether you're a Node.js developer entering AI engineering or an engineer building production LLM applications, this guide connects JavaScript backend development with the practical realities of modern generative AI. Build smarter backends. Engineer more reliable LLM applications.Bring intelligent systems to life with Node.js. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9798172784033
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Intelligent Systems Engineering : Empowering the Node.js Backend with Natural Language Processing with LLM
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Taschenbuch. Zustand: Neu. Neuware - Your Node.js backend can do far more than send requests to an LLM. It can become the foundation of a scalable, secure, intelligent AI application.Intelligent Systems Engineering explores how Node.js developers can move beyond basic API integrations and engineer production-ready applications powered by large language models and modern natural language processing.From connecting multiple LLM providers to building RAG pipelines, managing conversational memory, orchestrating AI agents, and controlling inference costs, this book focuses on the engineering decisions that matter when AI applications move from prototype to production.Inside, you'll explore: - OpenAI, Anthropic, and Google AI integrations with Node.js- Prompt engineering, structured outputs, and prompt-injection defenses- RAG pipelines, embeddings, vector databases, and semantic search- Redis-powered conversational memory and context management- Agentic workflows, function calling, MCP, and human-in-the-loop patterns- Semantic caching, batching, rate limiting, and token-cost optimization- PII protection, audit logging, privacy, and enterprise AI security- LLM testing, hallucination mitigation, RAG evaluation, and prompt benchmarking- High-concurrency architectures using WebSockets, SSE, containers, and serverless deploymentsWhether you're a Node.js developer entering AI engineering or an engineer building production LLM applications, this guide connects JavaScript backend development with the practical realities of modern generative AI. Build smarter backends. Engineer more reliable LLM applications.Bring intelligent systems to life with Node.js. Bestandsnummer des Verkäufers 9798172784033
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