Isbn: 9798171229702 - llms for software engineers: the math-free guide to large language models — transformers, embeddings, rag, and agents explained for developers (5 risultati)

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Taschenbuch. Condizione: Neu. Neuware - You know how to write software. You don't need another AI book that treats you like a ChatGPT tourist - and you definitely don't need one that opens with linear algebra.LLMs for Software Engineers is the missing middle: a complete, math-free explanation of how large language models actually work, written specifically for developers who want to build real applications with them - not derive backpropagation by hand.Using analogies you already understand from years of writing software - database joins, caching, lexers, hash maps, distributed systems - this book gives you genuine, durable mental models for the concepts every AI-adjacent engineering role now assumes you know: - How tokens, embeddings, and the transformer's attention mechanism actually work - no calculus required- The real difference between training and inference, and why a model can't 'just learn' from your conversation- How to build Retrieval-Augmented Generation (RAG) systems that ground LLM output in your own data- When to reach for prompting, RAG, or fine-tuning - and why treating them as interchangeable wastes time and money- How agents and function calling actually work under the hood, and how to build them reliably- Why hallucinations happen, and the concrete engineering mitigations that actually reduce them- How to evaluate LLM outputs, manage cost and latency, and defend against prompt injection in production systemsEvery chapter ends with a practical 'What This Means for You' takeaway, and a full glossary at the back means you can use this book as a working reference long after you've read it cover to cover.If you've been putting off learning 'the AI stuff' because every resource you've found is either a ChatGPT tutorial or a machine learning PhD textbook, this is the book that was actually missing.…

Paperback. Condizione: new. Paperback. You know how to write software. You don't need another AI book that treats you like a ChatGPT tourist - and you definitely don't need one that opens with linear algebra.LLMs for Software Engineers is the missing middle: a complete, math-free explanation of how large language models actually work, written specifically for developers who want to build real applications with them - not derive backpropagation by hand.Using analogies you already understand from years of writing software - database joins, caching, lexers, hash maps, distributed systems - this book gives you genuine, durable mental models for the concepts every AI-adjacent engineering role now assumes you know: How tokens, embeddings, and the transformer's attention mechanism actually work - no calculus requiredThe real difference between training and inference, and why a model can't "just learn" from your conversationHow to build Retrieval-Augmented Generation (RAG) systems that ground LLM output in your own dataWhen to reach for prompting, RAG, or fine-tuning - and why treating them as interchangeable wastes time and moneyHow agents and function calling actually work under the hood, and how to build them reliablyWhy hallucinations happen, and the concrete engineering mitigations that actually reduce themHow to evaluate LLM outputs, manage cost and latency, and defend against prompt injection in production systemsEvery chapter ends with a practical "What This Means for You" takeaway, and a full glossary at the back means you can use this book as a working reference long after you've read it cover to cover.If you've been putting off learning "the AI stuff" because every resource you've found is either a ChatGPT tutorial or a machine learning PhD textbook, this is the book that was actually missing. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condizione: new. Paperback. You know how to write software. You don't need another AI book that treats you like a ChatGPT tourist - and you definitely don't need one that opens with linear algebra.LLMs for Software Engineers is the missing middle: a complete, math-free explanation of how large language models actually work, written specifically for developers who want to build real applications with them - not derive backpropagation by hand.Using analogies you already understand from years of writing software - database joins, caching, lexers, hash maps, distributed systems - this book gives you genuine, durable mental models for the concepts every AI-adjacent engineering role now assumes you know: How tokens, embeddings, and the transformer's attention mechanism actually work - no calculus requiredThe real difference between training and inference, and why a model can't "just learn" from your conversationHow to build Retrieval-Augmented Generation (RAG) systems that ground LLM output in your own dataWhen to reach for prompting, RAG, or fine-tuning - and why treating them as interchangeable wastes time and moneyHow agents and function calling actually work under the hood, and how to build them reliablyWhy hallucinations happen, and the concrete engineering mitigations that actually reduce themHow to evaluate LLM outputs, manage cost and latency, and defend against prompt injection in production systemsEvery chapter ends with a practical "What This Means for You" takeaway, and a full glossary at the back means you can use this book as a working reference long after you've read it cover to cover.If you've been putting off learning "the AI stuff" because every resource you've found is either a ChatGPT tutorial or a machine learning PhD textbook, this is the book that was actually missing. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…