Building Applications with Large Language Models: Techniques, Implementation, and Applications - Softcover
Synopsis
This book delves into a broad spectrum of topics, covering the foundational aspects of Large Language Models (LLMs) such as PaLM, LLaMA, BERT, and GPT, among others.
The book takes you through the complexities involved in creating and deploying applications based on LLMs, providing you with an in-depth understanding of the model architecture. You will explore techniques such as fine-tuning, prompt engineering, and retrieval augmented generation (RAG). The book also addresses different ways to evaluate LLM outputs and discusses the benefits and limitations of large models. The book focuses on the tools, techniques, and methods essential for developing Large Language Models. It includes hands-on examples and tips to guide you in building applications using the latest technology in Natural Language Processing (NLP). It presents a roadmap to assist you in navigating challenges related to constructing and deploying LLM-based applications.
By the end of the book, you will understand LLMs and build applications with use cases that align with emerging business needs and address various problems in the realm of language processing.
What You Will Learn
- Be able to answer the question: What are Large Language Models?
- Understand techniques such as prompt engineering, fine-tuning, RAG, and vector databases
- Know the best practices for effective implementation
- Know the metrics and frameworks essential for evaluating the performance of Large Language Models
Who This Book Is For
An essential resource for AI-ML developers and enthusiasts eager to acquire practical, hands-on experience in this domain; also applies to individuals seeking a technical understanding of Large Language Models (LLMs) and those aiming to build applications using LLMs
"synopsis" may belong to another edition of this title.
About the Author
Bhawna Singh, a Data Scientist at CeADAR (UCD), holds both a bachelor and master degree in computer science. During her master’s program, she conducted research focused on identifying gender bias in Energy Policy data across the European Union. With prior experience as a Data Scientist at Brightflag in Ireland and a Machine Learning Engineer at AISmartz in India, Bhawna brings a wealth of expertise from both industry and academia. Her current research interests center on exploring diverse applications of Large Language Models. Over the course of her career, Bhawna has built models on extensive datasets, contributing to the development of intelligent systems addressing challenges such as customer churn, propensity prediction, sales forecasting, recommendation engines, customer segmentation, pdf validation, and more. She is dedicated to creating AI systems that are accessible to everyone, promoting inclusivity regardless of race, gender, social status, or language.
From the Back Cover
This book delves into a broad spectrum of topics, covering the foundational aspects of Large Language Models (LLMs) such as PaLM, LLaMA, BERT, and GPT, among others.
The book takes you through the complexities involved in creating and deploying applications based on LLMs, providing you with an in-depth understanding of the model architecture. You will explore techniques such as fine-tuning, prompt engineering, and retrieval augmented generation (RAG). The book also addresses different ways to evaluate LLM outputs and discusses the benefits and limitations of large models. The book focuses on the tools, techniques, and methods essential for developing Large Language Models. It includes hands-on examples and tips to guide you in building applications using the latest technology in Natural Language Processing (NLP). It presents a roadmap to assist you in navigating challenges related to constructing and deploying LLM-based applications.
By the end of the book, you will understand LLMs and build applications with use cases that align with emerging business needs and address various problems in the realm of language processing.
What You Will Learn
- Be able to answer the question: What are Large Language Models?
- Understand techniques such as prompt engineering, fine-tuning, RAG, and vector databases
- Know the best practices for effective implementation
- Know the metrics and frameworks essential for evaluating the performance of Large Language Models
"About this title" may belong to another edition of this title.
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Building Applications With Large Language Models : Techniques, Implementation and Applications
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Building Applications with Large Language Models
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Paperback. Condition: New. This book delves into a broad spectrum of topics, covering the foundational aspects of Large Language Models (LLMs) such as PaLM, LLaMA, BERT, and GPT, among others. The book takes you through the complexities involved in creating and deploying applications based on LLMs, providing you with an in-depth understanding of the model architecture. You will explore techniques such as fine-tuning, prompt engineering, and retrieval augmented generation (RAG). The book also addresses different ways to evaluate LLM outputs and discusses the benefits and limitations of large models. The book focuses on the tools, techniques, and methods essential for developing Large Language Models. It includes hands-on examples and tips to guide you in building applications using the latest technology in Natural Language Processing (NLP). It presents a roadmap to assist you in navigating challenges related to constructing and deploying LLM-based applications. By the end of the book, you will understand LLMs and build applications with use cases that align with emerging business needs and address various problems in the realm of language processing. What You Will LearnBe able to answer the question: What are Large Language Models?Understand techniques such as prompt engineering, fine-tuning, RAG, and vector databasesKnow the best practices for effective implementationKnow the metrics and frameworks essential for evaluating the performance of Large Language Models Who This Book Is ForAn essential resource for AI-ML developers and enthusiasts eager to acquire practical, hands-on experience in this domain; also applies to individuals seeking a technical understanding of Large Language Models (LLMs) and those aiming to build applications using LLMs. Seller Inventory # LU-9798868805684
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Building Applications with Large Language Models
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Paperback. Condition: New. This book delves into a broad spectrum of topics, covering the foundational aspects of Large Language Models (LLMs) such as PaLM, LLaMA, BERT, and GPT, among others. The book takes you through the complexities involved in creating and deploying applications based on LLMs, providing you with an in-depth understanding of the model architecture. You will explore techniques such as fine-tuning, prompt engineering, and retrieval augmented generation (RAG). The book also addresses different ways to evaluate LLM outputs and discusses the benefits and limitations of large models. The book focuses on the tools, techniques, and methods essential for developing Large Language Models. It includes hands-on examples and tips to guide you in building applications using the latest technology in Natural Language Processing (NLP). It presents a roadmap to assist you in navigating challenges related to constructing and deploying LLM-based applications. By the end of the book, you will understand LLMs and build applications with use cases that align with emerging business needs and address various problems in the realm of language processing. What You Will LearnBe able to answer the question: What are Large Language Models?Understand techniques such as prompt engineering, fine-tuning, RAG, and vector databasesKnow the best practices for effective implementationKnow the metrics and frameworks essential for evaluating the performance of Large Language Models Who This Book Is ForAn essential resource for AI-ML developers and enthusiasts eager to acquire practical, hands-on experience in this domain; also applies to individuals seeking a technical understanding of Large Language Models (LLMs) and those aiming to build applications using LLMs. Seller Inventory # LU-9798868805684
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book delves into a broad spectrum of topics, covering the foundational aspects of Large Language Models (LLMs) such as PaLM, LLaMA, BERT, and GPT, among others.The book takes you through the complexities involved in creating and deploying applications based on LLMs, providing you with an in-depth understanding of the model architecture. You will explore techniques such as fine-tuning, prompt engineering, and retrieval augmented generation (RAG). The book also addresses different ways to evaluate LLM outputs and discusses the benefits and limitations of large models. The book focuses on the tools, techniques, and methods essential for developing Large Language Models. It includes hands-on examples and tips to guide you in building applications using the latest technology in Natural Language Processing (NLP). It presents a roadmap to assist you in navigating challenges related to constructing and deploying LLM-based applications.By the end of the book, you will understand LLMs and build applications with use cases that align with emerging business needs and address various problems in the realm of language processing.What You Will LearnBe able to answer the question: What are Large Language Models Understand techniques such asprompt engineering, fine-tuning, RAG, and vector databasesKnowthe best practices for effective implementationKnow the metrics and frameworks essential for evaluating the performance of Large Language ModelsWho This Book Is ForAn essential resource for AI-ML developers and enthusiasts eager to acquire practical, hands-on experience in this domain; also applies to individuals seeking a technical understanding of Large Language Models (LLMs) and those aiming to build applications using LLMs 300 pp. Englisch. Seller Inventory # 9798868805684
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Building Applications with Large Language Models
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Paperback. Condition: New. This book delves into a broad spectrum of topics, covering the foundational aspects of Large Language Models (LLMs) such as PaLM, LLaMA, BERT, and GPT, among others. The book takes you through the complexities involved in creating and deploying applications based on LLMs, providing you with an in-depth understanding of the model architecture. You will explore techniques such as fine-tuning, prompt engineering, and retrieval augmented generation (RAG). The book also addresses different ways to evaluate LLM outputs and discusses the benefits and limitations of large models. The book focuses on the tools, techniques, and methods essential for developing Large Language Models. It includes hands-on examples and tips to guide you in building applications using the latest technology in Natural Language Processing (NLP). It presents a roadmap to assist you in navigating challenges related to constructing and deploying LLM-based applications. By the end of the book, you will understand LLMs and build applications with use cases that align with emerging business needs and address various problems in the realm of language processing. What You Will LearnBe able to answer the question: What are Large Language Models?Understand techniques such as prompt engineering, fine-tuning, RAG, and vector databasesKnow the best practices for effective implementationKnow the metrics and frameworks essential for evaluating the performance of Large Language Models Who This Book Is ForAn essential resource for AI-ML developers and enthusiasts eager to acquire practical, hands-on experience in this domain; also applies to individuals seeking a technical understanding of Large Language Models (LLMs) and those aiming to build applications using LLMs. Seller Inventory # LU-9798868805684
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ISBN 13: 9798868805684
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Paperback. Condition: new. Paperback. This book delves into a broad spectrum of topics, covering the foundational aspects of Large Language Models (LLMs) such as PaLM, LLaMA, BERT, and GPT, among others. The book takes you through the complexities involved in creating and deploying applications based on LLMs, providing you with an in-depth understanding of the model architecture. You will explore techniques such as fine-tuning, prompt engineering, and retrieval augmented generation (RAG). The book also addresses different ways to evaluate LLM outputs and discusses the benefits and limitations of large models. The book focuses on the tools, techniques, and methods essential for developing Large Language Models. It includes hands-on examples and tips to guide you in building applications using the latest technology in Natural Language Processing (NLP). It presents a roadmap to assist you in navigating challenges related to constructing and deploying LLM-based applications. By the end of the book, you will understand LLMs and build applications with use cases that align with emerging business needs and address various problems in the realm of language processing. What You Will LearnBe able to answer the question: What are Large Language Models?Understand techniques such as prompt engineering, fine-tuning, RAG, and vector databasesKnow the best practices for effective implementationKnow the metrics and frameworks essential for evaluating the performance of Large Language Models Who This Book Is ForAn essential resource for AI-ML developers and enthusiasts eager to acquire practical, hands-on experience in this domain; also applies to individuals seeking a technical understanding of Large Language Models (LLMs) and those aiming to build applications using LLMs This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798868805684
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