Grigorov Dilyan (36 results)

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Paperback. Condition: New. Gain a solid foundation for Natural Language Processing (NLP) and Large Language Models (LLMs), emphasizing their significance in today's computational world. This book is an introductory guide to NLP and LLMs with Python programming.The book starts with the basics of NLP and LLMs. It covers essential NLP concepts, such as text preprocessing, feature engineering, and sentiment analysis using Python. The book offers insights into Python programming, covering syntax, data types, conditionals, loops, functions, and object-oriented programming. Next, it delves deeper into LLMs, unraveling their complex components.You'll learn about LLM elements, including embedding layers, feedforward layers, recurrent layers, and attention mechanisms. You'll also explore important topics like tokens, token distributions, zero-shot learning, LLM hallucinations, and insights into popular LLM architectures such as GPT-4, BERT, T5, PALM, and others. Additionally, it covers Python libraries like Hugging Face, OpenAI API, and Cohere. The final chapter bridges theory with practical application, offering step-by-step examples of coded applications for tasks like text generation, summarization, language translation, question-answering systems, and chatbots.In the end, this book will equip you with the knowledge and tools to navigate the dynamic landscape of NLP and LLMs.What You'll LearnUnderstand the basics of Python and the features of Python 3.11Explore the essentials of NLP and how do they lay the foundations for LLMs.Review LLM components.Develop basic apps using LLMs and Python.Who This Book Is ForData analysts, AI and Machine Learning Experts, Python developers, and Software Development Professionals interested in learning the foundations of NLP, LLMs, and the processes of building modern LLM applications for various tasks.

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Paperback. Condition: new. Paperback. Harness the power of Large Language Models (LLMs) to build cutting-edge AI applications with Python and LangChain. This book provides a hands-on approach to understanding, implementing, and deploying LLM-powered solutions, equipping developers, data scientists, and AI enthusiasts with the tools to create real-world AI applications.The journey begins with an introduction to LangChain, covering its core concepts, integration with Python, and essential components such as prompt engineering, memory management, and retrieval-augmented generation (RAG). As you progress, youll explore advanced AI workflows, including multi-agent architectures, fine-tuning strategies, and optimization techniques to maximize LLM efficiency.The book also takes a deep dive into practical applications of LLMs, guiding you through the development of intelligent chatbots, document retrieval systems, content generation pipelines, and AI-driven automation tools. Youll learn how to leverage APIs, integrate LLMs into web and mobile platforms, and optimize large-scale deployments while addressing key challenges such as inference latency, cost efficiency, and ethical considerations.By the end of the book, youll have gained a solid understanding of LLM architectures, hands-on experience with LangChain, and the expertise to build scalable AI applications that redefine human-computer interaction. What You Will LearnUnderstand the fundamentals of LangChain and Python for LLM developmentKnow advanced AI workflows, including fine-tuning and memory managementBuild AI-powered applications such as chatbots, retrieval systems, and automation toolsKnow deployment strategies and performance optimization for real-world useUse best practices for scalability, security, and responsible AI implementationUnlock the full potential of LLMs and take your AI development skills to the next level Who This Book Is ForSoftware engineers and Python developers interested in learning the foundations of LLMs and building advanced modern LLM applications for various tasks mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: 'Times New Roman'; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: 'Times New Roman'; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: 'Times New Roman'; mso-fareast-font-family: 'Times New Roman'; Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

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Taschenbuch. Condition: Neu. Neuware -Gain a solid foundation for Natural Language Processing (NLP) and Large Language Models (LLMs), emphasizing their significance in today¿s computational world. This book is an introductory guide to NLP and LLMs with Python programming.The book starts with the basics of NLP and LLMs. It covers essential NLP concepts, such as text preprocessing, feature engineering, and sentiment analysis using Python. The book offers insights into Python programming, covering syntax, data types, conditionals, loops, functions, and object-oriented programming. Next, it delves deeper into LLMs, unraveling their complex components.Yoüll learn about LLM elements, including embedding layers, feedforward layers, recurrent layers, and attention mechanisms. Yoüll also explore important topics like tokens, token distributions, zero-shot learning, LLM hallucinations, and insights into popular LLM architectures such as GPT-4, BERT, T5, PALM, and others. Additionally, it covers Python libraries like Hugging Face, OpenAI API, and Cohere. The final chapter bridges theory with practical application, offering step-by-step examples of coded applications for tasks like text generation, summarization, language translation, question-answering systems, and chatbots.In the end, this book will equip you with the knowledge and tools to navigate the dynamic landscape of NLP and LLMs.What Yoüll LearnUnderstand the basics of Python and the features of Python 3.11Explore the essentials of NLP and how do they lay the foundations for LLMs.Review LLM components.Develop basic apps using LLMs and Python.Who This Book Is ForData analysts, AI and Machine Learning Experts, Python developers, and Software Development Professionals interested in learning the foundations of NLP, LLMs, and the processes of building modern LLM applications for various tasks.APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin 404 pp. Englisch.

Paperback. Condition: New. Gain a solid foundation for Natural Language Processing (NLP) and Large Language Models (LLMs), emphasizing their significance in today's computational world. This book is an introductory guide to NLP and LLMs with Python programming.The book starts with the basics of NLP and LLMs. It covers essential NLP concepts, such as text preprocessing, feature engineering, and sentiment analysis using Python. The book offers insights into Python programming, covering syntax, data types, conditionals, loops, functions, and object-oriented programming. Next, it delves deeper into LLMs, unraveling their complex components.You'll learn about LLM elements, including embedding layers, feedforward layers, recurrent layers, and attention mechanisms. You'll also explore important topics like tokens, token distributions, zero-shot learning, LLM hallucinations, and insights into popular LLM architectures such as GPT-4, BERT, T5, PALM, and others. Additionally, it covers Python libraries like Hugging Face, OpenAI API, and Cohere. The final chapter bridges theory with practical application, offering step-by-step examples of coded applications for tasks like text generation, summarization, language translation, question-answering systems, and chatbots.In the end, this book will equip you with the knowledge and tools to navigate the dynamic landscape of NLP and LLMs.What You'll LearnUnderstand the basics of Python and the features of Python 3.11Explore the essentials of NLP and how do they lay the foundations for LLMs.Review LLM components.Develop basic apps using LLMs and Python.Who This Book Is ForData analysts, AI and Machine Learning Experts, Python developers, and Software Development Professionals interested in learning the foundations of NLP, LLMs, and the processes of building modern LLM applications for various tasks.

Paperback. Condition: new. Paperback. Harness the power of Large Language Models (LLMs) to build cutting-edge AI applications with Python and LangChain. This book provides a hands-on approach to understanding, implementing, and deploying LLM-powered solutions, equipping developers, data scientists, and AI enthusiasts with the tools to create real-world AI applications.The journey begins with an introduction to LangChain, covering its core concepts, integration with Python, and essential components such as prompt engineering, memory management, and retrieval-augmented generation (RAG). As you progress, youll explore advanced AI workflows, including multi-agent architectures, fine-tuning strategies, and optimization techniques to maximize LLM efficiency.The book also takes a deep dive into practical applications of LLMs, guiding you through the development of intelligent chatbots, document retrieval systems, content generation pipelines, and AI-driven automation tools. Youll learn how to leverage APIs, integrate LLMs into web and mobile platforms, and optimize large-scale deployments while addressing key challenges such as inference latency, cost efficiency, and ethical considerations.By the end of the book, youll have gained a solid understanding of LLM architectures, hands-on experience with LangChain, and the expertise to build scalable AI applications that redefine human-computer interaction. What You Will LearnUnderstand the fundamentals of LangChain and Python for LLM developmentKnow advanced AI workflows, including fine-tuning and memory managementBuild AI-powered applications such as chatbots, retrieval systems, and automation toolsKnow deployment strategies and performance optimization for real-world useUse best practices for scalability, security, and responsible AI implementationUnlock the full potential of LLMs and take your AI development skills to the next level Who This Book Is ForSoftware engineers and Python developers interested in learning the foundations of LLMs and building advanced modern LLM applications for various tasks mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: 'Times New Roman'; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: 'Times New Roman'; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: 'Times New Roman'; mso-fareast-font-family: 'Times New Roman'; This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Harness the power of Large Language Models (LLMs) to build cutting-edge AI applications with Python and LangChain. This book provides a hands-on approach to understanding, implementing, and deploying LLM-powered solutions, equipping developers, data scientists, and AI enthusiasts with the tools to create real-world AI applications.The journey begins with an introduction to LangChain, covering its core concepts, integration with Python, and essential components such as prompt engineering, memory management, and retrieval-augmented generation (RAG). As you progress, you ll explore advanced AI workflows, including multi-agent architectures, fine-tuning strategies, and optimization techniques to maximize LLM efficiency.The book also takes a deep dive into practical applications of LLMs, guiding you through the development of intelligent chatbots, document retrieval systems, content generation pipelines, and AI-driven automation tools. You ll learn how to leverage APIs, integrate LLMs into web and mobile platforms, and optimize large-scale deployments while addressing key challenges such as inference latency, cost efficiency, and ethical considerations.By the end of the book, you ll have gained a solid understanding of LLM architectures, hands-on experience with LangChain, and the expertise to build scalable AI applications that redefine human-computer interaction.What You Will LearnUnderstand the fundamentals of LangChain and Python for LLM development 348 pp. Englisch.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Gain a solid foundation for Natural Language Processing (NLP) and Large Language Models (LLMs), emphasizing their significance in today's computational world. This book is an introductory guide to NLP and LLMs with Python programming.The book starts with the basics of NLP and LLMs. It covers essential NLP concepts, such as text preprocessing, feature engineering, and sentiment analysis using Python. The book offers insights into Python programming, covering syntax, data types, conditionals, loops, functions, and object-oriented programming. Next, it delves deeper into LLMs, unraveling their complex components.You'll learn about LLM elements, including embedding layers, feedforward layers, recurrent layers, and attention mechanisms. You'll also explore important topics like tokens, token distributions, zero-shot learning, LLM hallucinations, and insights into popular LLM architectures such as GPT-4, BERT, T5, PALM, and others. Additionally, it covers Python libraries like Hugging Face, OpenAI API, and Cohere. The final chapter bridges theory with practical application, offering step-by-step examples of coded applications for tasks like text generation, summarization, language translation, question-answering systems, and chatbots.In the end, this book will equip you with the knowledge and tools to navigate the dynamic landscape of NLP and LLMs.What You'll LearnUnderstand the basics of Python and the features of Python 3.11Explore the essentials of NLP and how do they lay the foundations for LLMs.Review LLM components.Develop basic apps using LLMs and Python.Who This Book Is ForData analysts, AI and Machine Learning Experts, Python developers, and Software Development Professionals interested in learning the foundations of NLP, LLMs, and the processes of building modern LLM applications for various tasks. 404 pp. Englisch.

Paperback. Condition: new. Paperback. Harness the power of Large Language Models (LLMs) to build cutting-edge AI applications with Python and LangChain. This book provides a hands-on approach to understanding, implementing, and deploying LLM-powered solutions, equipping developers, data scientists, and AI enthusiasts with the tools to create real-world AI applications.The journey begins with an introduction to LangChain, covering its core concepts, integration with Python, and essential components such as prompt engineering, memory management, and retrieval-augmented generation (RAG). As you progress, youll explore advanced AI workflows, including multi-agent architectures, fine-tuning strategies, and optimization techniques to maximize LLM efficiency.The book also takes a deep dive into practical applications of LLMs, guiding you through the development of intelligent chatbots, document retrieval systems, content generation pipelines, and AI-driven automation tools. Youll learn how to leverage APIs, integrate LLMs into web and mobile platforms, and optimize large-scale deployments while addressing key challenges such as inference latency, cost efficiency, and ethical considerations.By the end of the book, youll have gained a solid understanding of LLM architectures, hands-on experience with LangChain, and the expertise to build scalable AI applications that redefine human-computer interaction. What You Will LearnUnderstand the fundamentals of LangChain and Python for LLM developmentKnow advanced AI workflows, including fine-tuning and memory managementBuild AI-powered applications such as chatbots, retrieval systems, and automation toolsKnow deployment strategies and performance optimization for real-world useUse best practices for scalability, security, and responsible AI implementationUnlock the full potential of LLMs and take your AI development skills to the next level Who This Book Is ForSoftware engineers and Python developers interested in learning the foundations of LLMs and building advanced modern LLM applications for various tasks mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: 'Times New Roman'; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: 'Times New Roman'; mso-fareast-font-family: 'Times New Roman'; mso-bidi-font-family: 'Times New Roman'; mso-fareast-font-family: 'Times New Roman'; This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.

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