Building LLM Systems with RAG: From Deep Learning to Scalable Generative AI in Production with LangChain and Ollama - Couverture souple

Jafari, Ali

 
9798250073844: Building LLM Systems with RAG: From Deep Learning to Scalable Generative AI in Production with LangChain and Ollama
Couverture souple
ISBN 13 : 9798250073844
Editeur : Independently published, 2026

Synopsis

Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) are redefining how software systems are built. But most resources either focus on theory — or on shallow demos.

This book bridges the gap.

Building LLM Systems with RAG takes you from Machine Learning fundamentals to deploying scalable, production-ready Generative AI systems using modern tools like LangChain and Ollama.

This is not just another prompt engineering guide.

This is a system-building handbook.


What You’ll Learn

You will build a complete mental model of modern AI systems:

  • Foundations of Machine Learning and Deep Learning

  • Neural Networks, Transformers, and LLM architecture

  • Prompt Engineering techniques used in real systems

  • How RAG reduces hallucinations and improves reliability

  • Embeddings and vector databases

  • Chunking strategies that impact retrieval quality

  • Hybrid search (Sparse + Dense retrieval)

  • Reranking techniques for precision

  • Evaluating RAG systems properly

  • Designing production-ready LLM pipelines

  • Deploying scalable RAG systems using LangChain and Ollama

  • Running Local AI models securely and cost-effectively

By the end of this book, you won’t just understand LLMs — you’ll know how to build reliable AI systems around them.


Who This Book Is For

This book is for:

  • Software Engineers

  • Machine Learning Engineers

  • AI Architects

  • Technical Founders

  • Developers moving into Generative AI

You must know Python not Perfessional but minimum syntax understanding.

No PhD required — but curiosity and technical mindset are essential.


From Deep Learning to Production

You will move step-by-step:

Machine Learning
→ Deep Learning
→ Transformers
→ Large Language Models
→ Prompt Engineering
→ Basic RAG
→ Advanced RAG
→ Production Deployment

Each concept builds toward one goal:

Creating scalable, production-grade LLM systems.


What Makes This Book Different?

Unlike many AI books:

  • It focuses on systems, not just models

  • It explains why architectural decisions matter

  • It includes production engineering considerations

  • It combines theory with practical design

  • It uses real-world RAG pipelines

  • It integrates LangChain and Ollama for local AI

This book prepares you for the real world — not just the demo environment.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Éditeur
Independently published
Date d'édition
2026
Langue
anglais
ISBN 13 
9798250073844
Reliure
Tapa blanda
Nombre de pages
150
Coordonnées du fabricant
Manufactured by Amazon on behalf of the author
https://www.amazon.es/hz/contact-us

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Luxembourg