Mastering NLP From Foundations to Agents: Building AI Agents through Agentic Automation and RAG Workflows with Python , Second Edition

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Key benefits

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

Description

Natural 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 required

Who is this book for?

This 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.

What 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

What do you get with eBook?

Instant access to your Digital eBook purchase

Download this book in EPUB and PDF formats

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

AI Assistant (beta) to help accelerate your learning

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Mastering NLP From Foundations to Agents: Building AI Agents through Agentic Automation and RAG Workflows with Python , Second Edition

What do you get with eBook?