Mastering NLP From Foundations to Agents: Building AI Agents through Agentic Automation and RAG Workflows...

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Lior Gazit Meysam Ghaffari

Mastering NLP From Foundations to Agents

Name: Mastering NLP From Foundations to Agents
Price: 99.70 AUD
Availability: OutOfStock
ISBN: 9781806106134

Building AI Agents through Agentic Automation and RAG Workflows with Python

Lior Gazit, Meysam Ghaffari

$124.95 $99.70

Paperback

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English

Packt Publishing Limited
28 February 2026

Computing & IT

This second edition spans NLP foundations to LLMs, RAG, & agentic systems, teaching you to design and fine-tune production-ready AI solutions in Python. Free with your book: DRM-free PDF version + access to Packt's next-gen Reader
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Key Features

Engineer NLP systems from ML foundations to LLM architectures Implement RAG pipelines, routing layers, and agent workflows Fine-tune and align LLMs using LoRA, RLHF, and DPO methods Design production-grade AI systems with governance and safety

Book DescriptionNatural Language Processing has evolved beyond rule-based systems and classical machine learning (ML). This second edition guides you through that transformation from mathematical and ML foundations to large language models, retrieval pipelines, agentic automation, and AI-native system design. It strengthens core NLP concepts while expanding into modern architectures such as transformers, parameter-efficient fine-tuning (LoRA and QLoRA), and alignment methods like RLHF and DPO. You’ll begin with essential linear algebra, probability, and ML principles before moving into text preprocessing, feature engineering, classification pipelines, and deep learning architectures. From there, the focus shifts to system design: building Retrieval-Augmented Generation (RAG) pipelines, implementing model routing strategies that balance cost and performance, and orchestrating structured multi-agent workflows. You'll also introduce structured interoperability patterns, including the Model Context Protocol (MCP). Governance and safety will be treated as architectural concerns, demonstrating how policy and compliance can be integrated directly into AI systems. By the end, you will have the tools to implement NLP techniques and be equipped to design, govern, and deploy intelligent systems built on them.
*Email sign-up and proof of purchase requiredWhat you will learn

Build strong NLP foundations in math and ML Engineer text classification and NLP pipelines Train and fine-tune modern LLM architectures Implement RAG systems with LangChain Orchestrate multiple AI agents and tools to solve complex tasks Evaluate NLP model performance and apply AI safety best practices Integrate external data and tools using Model Context Protocol (MCP) Fine-tune transformers with LoRA, QLoRA, and DPO techniques

Who this book is forThis book is for machine learning engineers, data scientists, and NLP practitioners looking to deepen their expertise and build advanced AI solutions. It also benefits professionals and researchers who want to apply the latest NLP and LLM techniques in real-world projects. Software engineers entering the AI field and tech enthusiasts keen on modern NLP advancements will find it valuable. A solid understanding of Python and basic Machine Learning concepts is assumed.

By: Lior Gazit, Meysam Ghaffari
Imprint: Packt Publishing Limited
Country of Publication: United Kingdom
Edition: 2nd Revised edition
Dimensions: Height: 235mm, Width: 191mm,
ISBN: 9781806106134
ISBN 10: 1806106132
Pages: 694
Publication Date: 28 February 2026
Audience: General/trade , ELT Advanced
Format: Paperback
Publisher's Status: Active

Lior Gazit is a highly skilled Machine Learning professional with a proven track record of success in building and leading teams drive business growth. He is an expert in Natural Language Processing and has successfully developed innovative Machine Learning pipelines and products. He holds a Master degree and has published in peer-reviewed journals and conferences. As a Senior Director of the Machine Learning group in the Financial sector, and a Principal Machine Learning Advisor at an emerging startup, Lior is a respected leader in the industry, with a wealth of knowledge and experience to share. With much passion and inspiration, Lior is dedicated to using Machine Learning to drive positive change and growth in his organizations. Meysam Ghaffari is a Senior Data Scientist with a strong background in Natural Language Processing and Deep Learning. Currently working at MSKCC, where he specialize in developing and improving Machine Learning and NLP models for healthcare problems. He has over 9 years of experience in Machine Learning and over 4 years of experience in NLP and Deep Learning. He received his Ph.D. in Computer Science from Florida State University, His MS in Computer Science - Artificial Intelligence from Isfahan University of Technology and his B.S. in Computer Science at Iran University of Science and Technology. He also worked as a post doctoral research associate at University of Wisconsin-Madison before joining MSKCC.