Building LLM Systems with RAG: From Deep Learning to Scalable Generative AI in Production with LangChain and Ollama
Language: English
Published by Independently published, 2026
- Softcover
- New
Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
AbeBooks seller since April 6, 2009
Condition: New
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- Title
- Building LLM Systems with RAG: From Deep Learning to Scalable Generative AI in Production with LangChain and Ollama
- Author
- Jafari, Ali
- Publisher
- Independently published
- Publication year
- 2026
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 13
- 9798250073844
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
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Neural Networks, Transformers, and LLM architecture
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Prompt Engineering techniques used in real systems
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How RAG reduces hallucinations and improves reliability
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Embeddings and vector databases
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Chunking strategies that impact retrieval quality
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Hybrid search (Sparse + Dense retrieval)
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Reranking techniques for precision
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Evaluating RAG systems properly
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Designing production-ready LLM pipelines
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Deploying scalable RAG systems using LangChain and Ollama
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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.
"Synopsis" may belong to another edition of this title.
GreatBookPrices
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AbeBooks seller since April 6, 2009
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