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

Jafari, Ali

 
9798250073844: Building LLM Systems with RAG: From Deep Learning to Scalable Generative AI in Production with LangChain and Ollama

Inhaltsangabe

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.

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