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Practical LLM Engineering with Python: Build AI Agents, RAG Pipelines, MCP Servers, and Production AI Applications - Couverture souple
Synopsis
Build Real AI Applications — Not Toy Projects
You don’t need a PhD to build production AI systems.
You need working code, real engineering patterns, and practical guidance from someone who has actually shipped AI applications in the real world.
Practical LLM Engineering with Python is a hands-on guide designed for developers who want to build modern AI applications fast — without drowning in academic theory or hype.
Inside This Book, You’ll Learn How To:
- Work with OpenAI, Claude, and Gemini APIs
- Build RAG pipelines using ChromaDB, FAISS, and Pinecone
- Create AI agents with LangGraph
- Develop multi-agent systems using CrewAI
- Build MCP servers from scratch
- Deploy AI applications with FastAPI and Docker
- Add observability and tracing with LangSmith
- Structure scalable AI engineering workflows in Python
What Makes This Book Different?
Every concept is explained through real, executable code.
No academic fluff. No fake projects. No incomplete examples hidden behind GitHub repositories.
Every implementation is fully explained, practical, and designed to help you build deployable AI systems you can actually use in production.
Who This Book Is For
- Python developers entering AI engineering
- Data engineers integrating LLMs into modern pipelines
- Software engineers building AI products
- Freelancers and entrepreneurs creating AI-powered applications
- Developers who learn best by building
By the end of this book, you won’t just understand LLM engineering.
You’ll have a portfolio of real AI applications you can deploy, showcase, monetize, and use professionally.
If you want a practical AI engineering book that stays open beside your editor while you code, this is the one.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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Practical LLM Engineering with Python (Paperback)
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Paperback. Etat : new. Paperback. Build Real AI Applications - Not Toy ProjectsYou don't need a PhD to build production AI systems.You need working code, real engineering patterns, and practical guidance from someone who has actually shipped AI applications in the real world.Practical LLM Engineering with Python is a hands-on guide designed for developers who want to build modern AI applications fast - without drowning in academic theory or hype. Inside This Book, You'll Learn How To: Work with OpenAI, Claude, and Gemini APIsBuild RAG pipelines using ChromaDB, FAISS, and PineconeCreate AI agents with LangGraphDevelop multi-agent systems using CrewAIBuild MCP servers from scratchDeploy AI applications with FastAPI and DockerAdd observability and tracing with LangSmithStructure scalable AI engineering workflows in Python What Makes This Book Different?Every concept is explained through real, executable code.No academic fluff. No fake projects. No incomplete examples hidden behind GitHub repositories.Every implementation is fully explained, practical, and designed to help you build deployable AI systems you can actually use in production. Who This Book Is ForPython developers entering AI engineeringData engineers integrating LLMs into modern pipelinesSoftware engineers building AI productsFreelancers and entrepreneurs creating AI-powered applicationsDevelopers who learn best by building By the end of this book, you won't just understand LLM engineering.You'll have a portfolio of real AI applications you can deploy, showcase, monetize, and use professionally.If you want a practical AI engineering book that stays open beside your editor while you code, this is the one. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9798196028199
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Practical LLM Engineering with Python: Build AI Agents, RAG Pipelines, MCP Servers, and Production AI Applications
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Practical LLM Engineering with Python (Paperback)
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Paperback. Etat : new. Paperback. Build Real AI Applications - Not Toy ProjectsYou don't need a PhD to build production AI systems.You need working code, real engineering patterns, and practical guidance from someone who has actually shipped AI applications in the real world.Practical LLM Engineering with Python is a hands-on guide designed for developers who want to build modern AI applications fast - without drowning in academic theory or hype. Inside This Book, You'll Learn How To: Work with OpenAI, Claude, and Gemini APIsBuild RAG pipelines using ChromaDB, FAISS, and PineconeCreate AI agents with LangGraphDevelop multi-agent systems using CrewAIBuild MCP servers from scratchDeploy AI applications with FastAPI and DockerAdd observability and tracing with LangSmithStructure scalable AI engineering workflows in Python What Makes This Book Different?Every concept is explained through real, executable code.No academic fluff. No fake projects. No incomplete examples hidden behind GitHub repositories.Every implementation is fully explained, practical, and designed to help you build deployable AI systems you can actually use in production. Who This Book Is ForPython developers entering AI engineeringData engineers integrating LLMs into modern pipelinesSoftware engineers building AI productsFreelancers and entrepreneurs creating AI-powered applicationsDevelopers who learn best by building By the end of this book, you won't just understand LLM engineering.You'll have a portfolio of real AI applications you can deploy, showcase, monetize, and use professionally.If you want a practical AI engineering book that stays open beside your editor while you code, this is the one. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9798196028199
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Practical LLM Engineering with Python : Build AI Agents, RAG Pipelines, MCP Servers, and Production AI Applications
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Taschenbuch. Etat : Neu. Neuware - Build Real AI Applications - Not Toy ProjectsYou don't need a PhD to build production AI systems.You need working code, real engineering patterns, and practical guidance from someone who has actually shipped AI applications in the real world.Practical LLM Engineering with Python is a hands-on guide designed for developers who want to build modern AI applications fast - without drowning in academic theory or hype. Inside This Book, You'll Learn How To: - Work with OpenAI, Claude, and Gemini APIs- Build RAG pipelines using ChromaDB, FAISS, and Pinecone- Create AI agents with LangGraph- Develop multi-agent systems using CrewAI- Build MCP servers from scratch- Deploy AI applications with FastAPI and Docker- Add observability and tracing with LangSmith- Structure scalable AI engineering workflows in Python What Makes This Book Different Every concept is explained through real, executable code.No academic fluff. No fake projects. No incomplete examples hidden behind GitHub repositories.Every implementation is fully explained, practical, and designed to help you build deployable AI systems you can actually use in production. Who This Book Is For- Python developers entering AI engineering- Data engineers integrating LLMs into modern pipelines- Software engineers building AI products- Freelancers and entrepreneurs creating AI-powered applications- Developers who learn best by building By the end of this book, you won't just understand LLM engineering.You'll have a portfolio of real AI applications you can deploy, showcase, monetize, and use professionally.If you want a practical AI engineering book that stays open beside your editor while you code, this is the one. N° de réf. du vendeur 9798196028199
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