Generative large language models (76 Ergebnisse)

Zustand: New. In English.

Paperback. Zustand: Very Good. The definitive guide to LLMs, from architectures, pretraining, and fine-tuning to Retrieval Augmented Generation (RAG), multimodal AI, risk mitigation, and practical implementations with ChatGPT, Hugging Face, and Vertex AI Get With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader Free Key Features Compare and contrast 20+ models (including GPT, BERT, and Llama) and multiple platforms and libraries to find the right solution for your project Apply RAG with LLMs using customized texts and embeddings Mitigate LLM risks, such as hallucinations, using moderation models and knowledge bases Book DescriptionTransformers for Natural Language Processing and Computer Vision, Third Edition, explores Large Language Model (LLM) architectures, practical applications, and popular platforms (Hugging Face, OpenAI, and Google Vertex AI) used for Natural Language Processing (NLP) and Computer Vision (CV). The book guides you through a range of transformer architectures from foundation models and generative AI. You?ll pretrain and fine-tune LLMs and work through different use cases, from summarization to question-answering systems leveraging embedding-based search. You'll also implement Retrieval Augmented Generation (RAG) to enhance accuracy and gain greater control over your LLM outputs. Additionally, you?ll understand common LLM risks, such as hallucinations, memorization, and privacy issues, and implement mitigation strategies using moderation models alongside rule-based systems and knowledge integration. Dive into generative vision transformers and multimodal architectures, and build practical applications, such as image and video classification. Go further and combine different models and platforms to build AI solutions and explore AI agent capabilities. This book provides you with an understanding of transformer architectures, including strategies for pretraining, fine-tuning, and LLM best practices.What you will learn Breakdown and understand the architectures of the Transformer, BERT, GPT, T5, PaLM, ViT, CLIP, and DALL-E Fine-tune BERT, GPT, and PaLM models Learn about different tokenizers and the best practices for preprocessing language data Pretrain a RoBERTa model from scratch Implement retrieval augmented generation and rules bases to mitigate hallucinations Visualize transformer model activity for deeper insights using BertViz, LIME, and SHAP Go in-depth into vision transformers with CLIP, DALL-E, and GPT Who this book is forThis book is ideal for NLP and CV engineers, data scientists, machine learning practitioners, software developers, and technical leaders looking to advance their expertise in LLMs and generative AI or explore latest industry trends. Familiarity with Python and basic machine learning concepts will help you fully understand the use cases and code examples. However, hands-on examples involving LLM user interfaces, prompt engineering, and no-code model building ensure this book remains accessible to anyone curious about the AI revolution. …

Paperback. Zustand: Good. The definitive guide to LLMs, from architectures, pretraining, and fine-tuning to Retrieval Augmented Generation (RAG), multimodal AI, risk mitigation, and practical implementations with ChatGPT, Hugging Face, and Vertex AI Get With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader Free Key Features Compare and contrast 20+ models (including GPT, BERT, and Llama) and multiple platforms and libraries to find the right solution for your project Apply RAG with LLMs using customized texts and embeddings Mitigate LLM risks, such as hallucinations, using moderation models and knowledge bases Book DescriptionTransformers for Natural Language Processing and Computer Vision, Third Edition, explores Large Language Model (LLM) architectures, practical applications, and popular platforms (Hugging Face, OpenAI, and Google Vertex AI) used for Natural Language Processing (NLP) and Computer Vision (CV). The book guides you through a range of transformer architectures from foundation models and generative AI. You?ll pretrain and fine-tune LLMs and work through different use cases, from summarization to question-answering systems leveraging embedding-based search. You'll also implement Retrieval Augmented Generation (RAG) to enhance accuracy and gain greater control over your LLM outputs. Additionally, you?ll understand common LLM risks, such as hallucinations, memorization, and privacy issues, and implement mitigation strategies using moderation models alongside rule-based systems and knowledge integration. Dive into generative vision transformers and multimodal architectures, and build practical applications, such as image and video classification. Go further and combine different models and platforms to build AI solutions and explore AI agent capabilities. This book provides you with an understanding of transformer architectures, including strategies for pretraining, fine-tuning, and LLM best practices.What you will learn Breakdown and understand the architectures of the Transformer, BERT, GPT, T5, PaLM, ViT, CLIP, and DALL-E Fine-tune BERT, GPT, and PaLM models Learn about different tokenizers and the best practices for preprocessing language data Pretrain a RoBERTa model from scratch Implement retrieval augmented generation and rules bases to mitigate hallucinations Visualize transformer model activity for deeper insights using BertViz, LIME, and SHAP Go in-depth into vision transformers with CLIP, DALL-E, and GPT Who this book is forThis book is ideal for NLP and CV engineers, data scientists, machine learning practitioners, software developers, and technical leaders looking to advance their expertise in LLMs and generative AI or explore latest industry trends. Familiarity with Python and basic machine learning concepts will help you fully understand the use cases and code examples. However, hands-on examples involving LLM user interfaces, prompt engineering, and no-code model building ensure this book remains accessible to anyone curious about the AI revolution.…

Zustand: New. In English.

paperback. Zustand: Very Good.

paperback. Zustand: Fine.

Zustand: New. In English.

Paperback. Zustand: Fine.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

paperback. Zustand: Very Good.

Zustand: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.

Paperback. Zustand: Brand New. 9.45x0.43x6.22 inches. In Stock.

paperback. Zustand: Fine.

paperback. Zustand: Very Good.

paperback. Zustand: Very Good.

Soft cover. Zustand: New. Introduction to Large Language Models (LLMs) is a comprehensive guide for understanding the foundations and advancements of Generative AI for Text. Designed for educators and enthusiasts, the book starts with key linguistic concepts and progresses through NLP fundamentals from word embeddings to pretrained foundational models. Readers will learn how LLMs process and generate language, overcome limitations, and enhance performance using techniques like prompt engineering, retrieval-augmented generation, and human alignment. The book uniquely presents cutting-edge research in a concise format, enriched with visual aids, exercises, and practical resources. Ideal for computer science faculty, this resource offers both theoretical insights and real-world applications, showcasing how LLMs like ChatGPT are transforming technology and advancing AI innovation.…

Zustand: New. In English.

Zustand: New. In English.

Zustand: New. In English.

Zustand: New.

Zustand: New. In English.

Zustand: New. In English.

Zustand: New. In English.

Zustand: New.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Taschenbuch. Zustand: Neu. Neuware - In 2026, prompting is no longer a casual skill - it is a core engineering discipline that separates basic AI users from those who build reliable, scalable, and secure intelligent systems.AI Prompting Handbook is the definitive professional guide to mastering prompt engineering from fundamentals to production-grade applications. Written for developers, AI engineers, technical leaders, analysts, and power users, this handbook provides a complete, up-to-date framework for communicating effectively with today's most powerful large language models.Whether you are just beginning your journey or already building complex agentic systems, this book takes you step-by-step through the essential principles and advanced techniques that deliver consistent, measurable results across GPT-4o, Claude 4, Gemini, Grok, Llama, Mistral, and other frontier models.What You Will Master: - The five universal elements of every high-performing prompt- Foundational and advanced reasoning patterns, including Chain-of-Thought, ReAct, Tree of Thoughts, Reflexion, and Graph of Thoughts- Model-specific strategies to extract maximum performance from each major LLM provider- Production-ready agentic workflows with memory, planning, and tool use- Multimodal prompting techniques for images, video, documents, and charts- Systematic prompt evaluation, A/B testing, and automated optimization- Enterprise-grade security, prompt injection defense, and OWASP LLM risk mitigation- Real-world applications in software development, content creation, research, analysis, and strategic decision-makingPacked with practical examples, ready-to-use templates, before-and-after transformations, and hands-on exercises, this handbook serves as both a comprehensive learning path and a daily reference you will return to again and again.Written by Sammy Tech, AI Prompting Handbook delivers the depth and clarity expected from top technical publishers while remaining accessible and immediately applicable.The definitive 2026 guide to professional prompt engineering.Master the skill that powers modern AI systems - from prototype to production.…

Zustand: New. In English.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.