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{ "item_title" : "Large Language Models in Practice", "item_author" : [" Michael Harris "], "item_description" : "Most developers learn what LLMs can do. This book teaches you howto actually build with them. Large Language Models in Practice is a hands-on engineering guidefor developers who want to go beyond ChatGPT prompts and buildreal, production-ready AI systems from scratch, with working code. You'll start with the fundamentals transformers, tokenization,embeddings, attention and progressively move into the engineeringpatterns that power real-world AI products. Every concept is pairedwith Python code you can run, modify, and ship. What's inside: - How LLMs actually work under the hood transformers,self-attention, positional encoding, and next-token prediction- Working with LLM APIs authentication, context windows,streaming, cost management, and rate limits- Prompt engineering that works zero-shot, few-shot,chain-of-thought, role-based prompting, and reusable templates- Building real AI apps chatbots, summarizers, contentgenerators, and information extraction systems- Retrieval-Augmented Generation (RAG) vector databases,embeddings, document chunking, and full RAG pipelines- Fine-tuning open-source models for your specific use case- AI agents how to design, build, and orchestrate them- Production deployment scaling, monitoring, evaluation,and enterprise-grade architecture 10 hands-on projects including a PDF Q&A system, AI customersupport chatbot, personal research assistant, and a deployableenterprise AI assistant. This is not a theory textbook. This is the book you hand toa developer and say: build something real with it. Perfect for: software engineers, backend developers, technicalfounders, CS students, and self-taught developers who want tobuild serious AI systems no ML PhD required.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/9/79/818/246/9798182463218_b.jpg", "price_data" : { "retail_price" : "25.00", "online_price" : "25.00", "our_price" : "25.00", "club_price" : "25.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Large Language Models in Practice|Michael Harris

Large Language Models in Practice : How LLMs Work, How to Use Them, and How to Build Production-Ready AI Systems

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Overview

Most developers learn what LLMs can do. This book teaches you how
to actually build with them. Large Language Models in Practice is a hands-on engineering guide
for developers who want to go beyond ChatGPT prompts and build
real, production-ready AI systems from scratch, with working code. You'll start with the fundamentals transformers, tokenization,
embeddings, attention and progressively move into the engineering
patterns that power real-world AI products. Every concept is paired
with Python code you can run, modify, and ship. What's inside: - How LLMs actually work under the hood transformers,
self-attention, positional encoding, and next-token prediction
- Working with LLM APIs authentication, context windows,
streaming, cost management, and rate limits
- Prompt engineering that works zero-shot, few-shot,
chain-of-thought, role-based prompting, and reusable templates
- Building real AI apps chatbots, summarizers, content
generators, and information extraction systems
- Retrieval-Augmented Generation (RAG) vector databases,
embeddings, document chunking, and full RAG pipelines
- Fine-tuning open-source models for your specific use case
- AI agents how to design, build, and orchestrate them
- Production deployment scaling, monitoring, evaluation,
and enterprise-grade architecture 10 hands-on projects including a PDF Q&A system, AI customer
support chatbot, personal research assistant, and a deployable
enterprise AI assistant. This is not a theory textbook. This is the book you hand to
a developer and say: build something real with it. Perfect for: software engineers, backend developers, technical
founders, CS students, and self-taught developers who want to
build serious AI systems no ML PhD required.

This item is Non-Returnable

Details

  • ISBN-13: 9798182463218
  • ISBN-10: 9798182463218
  • Publisher: Independently Published
  • Publish Date: June 2026
  • Dimensions: 9 x 6 x 0.47 inches
  • Shipping Weight: 0.67 pounds
  • Page Count: 224

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