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.
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.
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.
"synopsis" may belong to another edition of this title.
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
Paperback. Condition: 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. Seller Inventory # 9798196028199
Seller: California Books, Miami, FL, U.S.A.
Condition: New. Print on Demand. Seller Inventory # I-9798196028199
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # L2-9798196028199
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Seller: CitiRetail, Stevenage, United Kingdom
Paperback. Condition: 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. Seller Inventory # 9798196028199
Quantity: 1 available
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: 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. Seller Inventory # 9798196028199
Quantity: 2 available
Seller: PBShop.store US, Wood Dale, IL, U.S.A.
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # L2-9798196028199