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Paperback or Softback. Condizione: New. Mastering NLP From Foundations to Agents - Second Edition: Building AI Agents through Agentic Automation and RAG Workflows with Python. Book.

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Paperback or Softback. Condizione: New. Mastering NLP from Foundations to LLMs: Apply advanced rule-based techniques to LLMs and solve real-world business problems using Python. Book.

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Paperback. Condizione: New. 2nd.

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Paperback. Condizione: New. 2nd. A fully updated second edition that bridges NLP fundamentals with the latest in AI. New chapters on LLMs, RAG, LangChain, and autonomous agents help you build advanced language solutions with hands-on Python examples.

Condizione: New. pp. 387.

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Paperback. Condizione: New. 2nd. A fully updated second edition that bridges NLP fundamentals with the latest in AI. New chapters on LLMs, RAG, LangChain, and autonomous agents help you build advanced language solutions with hands-on Python examples.

Paperback. Condizione: New. 2nd. A fully updated second edition that bridges NLP fundamentals with the latest in AI. New chapters on LLMs, RAG, LangChain, and autonomous agents help you build advanced language solutions with hands-on Python examples.

Paperback. Condizione: new. Paperback. 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*Key FeaturesEngineer NLP systems from ML foundations to LLM architecturesImplement RAG pipelines, routing layers, and agent workflowsFine-tune and align LLMs using LoRA, RLHF, and DPO methodsDesign production-grade AI systems with governance and safetyBook 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.Youll 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 learnBuild strong NLP foundations in math and MLEngineer text classification and NLP pipelinesTrain and fine-tune modern LLM architecturesImplement RAG systems with LangChainOrchestrate multiple AI agents and tools to solve complex tasksEvaluate NLP model performance and apply AI safety best practicesIntegrate external data and tools using Model Context Protocol (MCP)Fine-tune transformers with LoRA, QLoRA, and DPO techniquesWho 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback / softback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Paperback / softback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Condizione: New. Print on Demand pp. 387.

Condizione: New. Print on Demand.

Condizione: New. PRINT ON DEMAND pp. 387.

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Paperback. Condizione: new. Paperback. 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*Key FeaturesEngineer NLP systems from ML foundations to LLM architecturesImplement RAG pipelines, routing layers, and agent workflowsFine-tune and align LLMs using LoRA, RLHF, and DPO methodsDesign production-grade AI systems with governance and safetyBook 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.Youll 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 learnBuild strong NLP foundations in math and MLEngineer text classification and NLP pipelinesTrain and fine-tune modern LLM architecturesImplement RAG systems with LangChainOrchestrate multiple AI agents and tools to solve complex tasksEvaluate NLP model performance and apply AI safety best practicesIntegrate external data and tools using Model Context Protocol (MCP)Fine-tune transformers with LoRA, QLoRA, and DPO techniquesWho 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

Paperback. Condizione: new. Paperback. 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*Key FeaturesEngineer NLP systems from ML foundations to LLM architecturesImplement RAG pipelines, routing layers, and agent workflowsFine-tune and align LLMs using LoRA, RLHF, and DPO methodsDesign production-grade AI systems with governance and safetyBook 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.Youll 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 learnBuild strong NLP foundations in math and MLEngineer text classification and NLP pipelinesTrain and fine-tune modern LLM architecturesImplement RAG systems with LangChainOrchestrate multiple AI agents and tools to solve complex tasksEvaluate NLP model performance and apply AI safety best practicesIntegrate external data and tools using Model Context Protocol (MCP)Fine-tune transformers with LoRA, QLoRA, and DPO techniquesWho 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. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Taschenbuch. Condizione: Neu. Mastering NLP From Foundations to Agents - Second Edition | Building AI Agents through Agentic Automation and RAG Workflows with Python | Lior Gazit (u. a.) | Taschenbuch | Englisch | 2026 | Packt Publishing | EAN 9781806106134 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.