Developing Ai Applications With Large Language Models
DOWNLOAD
Download Developing Ai Applications With Large Language Models PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Developing Ai Applications With Large Language Models book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Developing Ai Applications With Large Language Models
DOWNLOAD
Author : Maria Johnsen
language : en
Publisher: Maria Johnsen
Release Date : 2025-01-18
Developing Ai Applications With Large Language Models written by Maria Johnsen and has been published by Maria Johnsen this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-18 with Computers categories.
In my previous book Large Language Models (LLms), I explained and discussed about the intricacies of Large Language Models (LLMs), giving readers a comprehensive understanding of these powerful technologies. This book takes that knowledge a step further, focusing on the practical side of developing AI applications using LLMs. It is designed to be a hands-on, step-by-step guide to building AI solutions. Over the years, I’ve been fascinated by the many possibilities AI offers, and I’ve come to realize that many people, from developers to researchers, want to build real-world applications but often don’t know where to start. That’s why I decided to write this book because I believe that with the right guidance, anyone can harness the full potential of LLMs to create meaningful and impactful AI-driven solutions. My book covers a wide range of practical applications, including in industries like healthcare, film production, music, video, and language translation. I also explore how AI can empower researchers and innovators in countless fields. By breaking down complex topics such as tokenization, attention mechanisms, and transformer architecture in an approachable way, I want to help you understand these essential concepts and how to apply them to build your own AI applications. Throughout this journey, you’ll learn not just how to set up your development environment and choose the right models, but also how to use the most powerful tools available to create applications like chatbots, virtual assistants, and much more. I’ve made sure to emphasize key aspects such as prompt engineering, fine-tuning pretrained models, and adapting LLMs to industries such as healthcare and finance, where they can make the most significant impact. But this book isn’t just about building great technology. It’s also about building responsible technology. I’ve dedicated a section to the ethical challenges that come with working in AI, such as bias and fairness, and I offer strategies for developing scalable AI applications that are both effective and ethical. The motivation behind writing this book is simple: I want to empower you to unlock the potential of LLMs in practical ways. I’ve had the privilege of exploring and developing with AI over the years, and I want to share that experience with you. Whether you’re a developer looking to expand your skills, a researcher trying to integrate AI into your work, or an entrepreneur hoping to revolutionize an industry, this book is meant to be your guide. This book is for anyone eager to explore the practical development of AI applications using Large Language Models. Whether you’re just getting started with AI or looking to enhance your skills, you’ll find something here that speaks to you. It’s particularly suited for: Developers who want to dive deeper into building AI applications, from chatbots to complex AI systems. Researchers who are looking to integrate LLMs into their projects for tasks like data analysis, language translation, or summarization. Industry professionals in fields like healthcare, finance, and entertainment who want to leverage AI to innovate and enhance their business. AI enthusiasts and students who are passionate about AI and want to build practical, real-world applications. By the end of this book, my hope is that you’ll feel confident not only in your understanding of how LLMs work, but also in your ability to apply them to create powerful, responsible AI applications across many different domains.
Developing Ai Applications With Large Language Models
DOWNLOAD
Author : Maria Johnsen
language : en
Publisher: Independently Published
Release Date : 2025-01-18
Developing Ai Applications With Large Language Models written by Maria Johnsen and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-18 with Computers categories.
In this book, I expand upon the concepts introduced in my previous book on Large Language Models (LLMs) by providing a comprehensive, step-by-step guide on how to create AI applications using LLMs. This book is specifically designed to help developers, data scientists, and AI enthusiasts build real-world AI solutions with the power of large language models. The book begins with an exploration of LLMs what they are, how they function, and the principles behind them. Key concepts such as tokenization, attention mechanisms, and transformer architecture are explained in detail to build a strong foundation for understanding how language models like GPT and BERT work. I provide practical guidance for setting up an AI development environment, selecting the right models, and choosing the best tools and frameworks to use when building applications. Ethical considerations are emphasized, ensuring that AI developers can create responsible, unbiased applications. Readers will learn how to develop various AI applications, from building chatbots to creating AI-powered virtual assistants and content creation tools. The book also covers prompt engineering, which is crucial for customizing and refining the behavior of LLMs, as well as techniques like few-shot and zero-shot learning to improve model output without needing vast amounts of data. A significant focus of the book is on fine-tuning pretrained models. It includes step-by-step instructions on preparing datasets, fine-tuning models using platforms like Hugging Face, and deploying models in real-world applications. The book also dives into optimization techniques for performance, cost-efficiency, and scaling AI solutions to handle large user bases. Chapters also highlight specialized AI applications in diverse sectors such as healthcare, education, finance, e-commerce, and creative industries. I discuss the unique challenges and opportunities within each field, offering practical examples of how LLMs are transforming these industries. Emerging trends, open-source contributions, and the future of LLMs are explored, providing readers with insight into the evolving landscape of AI. I also tackle challenges like model bias, fairness, and ethical regulation, offering strategies for overcoming these obstacles in AI development. "Developing AI Applications with Large Language Models" is a hands-on guide that empowers readers to successfully create scalable, effective, and ethical AI applications using the most advanced LLMs available, paving the way for future innovations in AI development.
Application Of Large Language Models Llms For Software Vulnerability Detection
DOWNLOAD
Author : Omar, Marwan
language : en
Publisher: IGI Global
Release Date : 2024-11-01
Application Of Large Language Models Llms For Software Vulnerability Detection written by Omar, Marwan and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-01 with Computers categories.
Large Language Models (LLMs) are redefining the landscape of cybersecurity, offering innovative methods for detecting software vulnerabilities. By applying advanced AI techniques to identify and predict weaknesses in software code, including zero-day exploits and complex malware, LLMs provide a proactive approach to securing digital environments. This integration of AI and cybersecurity presents new possibilities for enhancing software security measures. Application of Large Language Models (LLMs) for Software Vulnerability Detection offers a comprehensive exploration of this groundbreaking field. These chapters are designed to bridge the gap between AI research and practical application in cybersecurity, in order to provide valuable insights for researchers, AI specialists, software developers, and industry professionals. Through real-world examples and actionable strategies, the publication will drive innovation in vulnerability detection and set new standards for leveraging AI in cybersecurity.
The Llm Engineer S Playbook Mastering The Development Of Large Language Models For Real World Applications
DOWNLOAD
Author : Leona Lang
language : en
Publisher: DIGITAL BLUE INC.
Release Date : 2025-03-31
The Llm Engineer S Playbook Mastering The Development Of Large Language Models For Real World Applications written by Leona Lang and has been published by DIGITAL BLUE INC. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-31 with Computers categories.
The world of artificial intelligence is rapidly evolving, and at the heart of this revolution are Large Language Models (LLMs). These powerful tools are transforming how we interact with technology, offering unprecedented capabilities in natural language processing. The LLM Engineer's Playbook is an essential guide for anyone looking to navigate the complexities of developing and deploying LLMs in practical, real-world scenarios. This book provides a comprehensive roadmap for engineers, developers, and tech enthusiasts eager to harness the potential of LLMs, offering a blend of theoretical insights and hands-on techniques. Within these pages, you'll find a rich array of content designed to elevate your understanding and skills in LLM development. The book covers foundational concepts, ensuring even those new to the field can follow along, and progressively delves into more advanced topics. Key sections include the architecture and functioning of LLMs, data preparation and preprocessing, model training and fine-tuning, and best practices for deployment and maintenance. Each chapter is crafted to build on the previous one, creating a seamless learning experience. The practical examples and case studies illustrate how LLMs can be applied in various industries, from enhancing customer service chatbots to revolutionizing content creation and beyond.
Challenges In Large Language Model Development And Ai Ethics
DOWNLOAD
Author : Gupta, Brij
language : en
Publisher: IGI Global
Release Date : 2024-08-15
Challenges In Large Language Model Development And Ai Ethics written by Gupta, Brij and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-15 with Computers categories.
The development of large language models has resulted in artificial intelligence advancements promising transformations and benefits across various industries and sectors. However, this progress is not without its challenges. The scale and complexity of these models pose significant technical hurdles, including issues related to bias, transparency, and data privacy. As these models integrate into decision-making processes, ethical concerns about their societal impact, such as potential job displacement or harmful stereotype reinforcement, become more urgent. Addressing these challenges requires a collaborative effort from business owners, computer engineers, policymakers, and sociologists. Fostering effective research for solutions to address AI ethical challenges may ensure that large language model developments benefit society in a positive way. Challenges in Large Language Model Development and AI Ethics addresses complex ethical dilemmas and challenges of the development of large language models and artificial intelligence. It analyzes ethical considerations involved in the design and implementation of large language models, while exploring aspects like bias, accountability, privacy, and social impacts. This book covers topics such as law and policy, model architecture, and machine learning, and is a useful resource for computer engineers, sociologists, policymakers, business owners, academicians, researchers, and scientists.
Building Applications With Large Language Models
DOWNLOAD
Author : Bhawna Singh
language : en
Publisher: Springer Nature
Release Date : 2024-11-29
Building Applications With Large Language Models written by Bhawna Singh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-29 with Computers categories.
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
Designing Large Language Model Applications
DOWNLOAD
Author : Suhas Pai
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2025-03-06
Designing Large Language Model Applications written by Suhas Pai and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-06 with Computers categories.
Large language models (LLMs) have proven themselves to be powerful tools for solving a wide range of tasks, and enterprises have taken note. But transitioning from demos and prototypes to full-fledged applications can be difficult. This book helps close that gap, providing the tools, techniques, and playbooks that practitioners need to build useful products that incorporate the power of language models. Experienced ML researcher Suhas Pai offers practical advice on harnessing LLMs for your use cases and dealing with commonly observed failure modes. You’ll take a comprehensive deep dive into the ingredients that make up a language model, explore various techniques for customizing them such as fine-tuning, learn about application paradigms like RAG (retrieval-augmented generation) and agents, and more. Understand how to prepare datasets for training and fine-tuning Develop an intuition about the Transformer architecture and its variants Adapt pretrained language models to your own domain and use cases Learn effective techniques for fine-tuning, domain adaptation, and inference optimization Interface language models with external tools and data and integrate them into an existing software ecosystem
Large Language Models For Sustainable Urban Development
DOWNLOAD
Author : Nitin Liladhar Rane
language : en
Publisher: Springer Nature
Release Date : 2025-07-01
Large Language Models For Sustainable Urban Development written by Nitin Liladhar Rane and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-01 with Computers categories.
With rapid urbanization defining the 21st Century, cities face mounting challenges in achieving sustainability, equity, and functionality. This book explores how innovative technologies such as Artificial Intelligence (AI) and Large Language Models (LLMs) can transform urban development by offering intelligent, data-driven solutions. LLMs go beyond automation, acting as co-creators in addressing environmental sustainability, resource management, and equitable development. By analyzing regulations, best practices, and real-time data on phenomena such as air pollution and traffic, these models empower urban planners to design smarter, more sustainable cities while fostering collaboration across disciplines. Divided into five sections, the book explores the diverse applications of LLMs, from optimizing renewable energy systems and enhancing urban planning to revolutionizing construction practices and improving resource efficiency. It highlights case studies on integrating AI with smart infrastructure, ecological balance, and disaster resilience. While underscoring their transformative potential, the book also examines ethical considerations such as bias, privacy, and environmental impact. More than a collection of research, this work is a call to action for urban planners, data scientists, policymakers, and researchers to harness AI responsibly in building greener, more equitable urban futures.
Building Conversational Generative Ai Apps With Langchain And Gpt Develop End To End Llm Powered Conversational Ai Apps With Python Langchain Gpt And Google Colab
DOWNLOAD
Author : Mugesh S.
language : en
Publisher: Orange Education Pvt Limited
Release Date : 2025-06-04
Building Conversational Generative Ai Apps With Langchain And Gpt Develop End To End Llm Powered Conversational Ai Apps With Python Langchain Gpt And Google Colab written by Mugesh S. and has been published by Orange Education Pvt Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-04 with Computers categories.
Transform Text into Intelligent Conversations with LangChain and GPT. Key Features● Build AI Chatbots with LangChain, Python and GPT models through hands-on guidance.● Master Advanced Techniques like RAG, document embedding, and LLM fine-tuning.● Deploy and Scale conversational AI systems for real-world applications. Book DescriptionConversational AI Apps are revolutionizing the way we interact with technology, enabling businesses and developers to create smarter, more intuitive applications that engage users in natural, meaningful ways. Building Conversational Generative AI Apps with LangChain and GPT is your ultimate guide to mastering AI-driven conversational systems. Starting with core concepts of generative AI and LLMs, you'll learn to build intelligent chatbots and virtual assistants, while exploring techniques like fine-tuning LLMs, retrieval-augmented generation (RAG), and document embedding. As you progress, you'll dive deeper into advanced topics such as vector databases and multimodal capabilities, enabling you to create highly accurate, context-aware AI agents. The book's step-by-step tutorials ensure that you develop practical skills in deploying and optimizing scalable conversational AI solutions. By the end, you'll be equipped to build AI apps that enhance customer engagement, automate workflows, and scale seamlessly. Unlock the potential of Building Conversational Generative AI Apps with LangChain and GPT and create next-gen AI applications today! What you will learn● Build and deploy AI-driven chatbots using LangChain and GPT models.● Implement advanced techniques like retrieval-augmented generation (RAG) for smarter responses.● Fine-tune LLMs for domain-specific conversational AI applications.● Leverage vector databases for efficient knowledge retrieval and enhanced chatbot performance.● Explore multimodal capabilities and document embedding for better context-aware responses.● Optimize and scale conversational AI systems for large-scale deployments.
Advancing Software Engineering Through Ai Federated Learning And Large Language Models
DOWNLOAD
Author : Sharma, Avinash Kumar
language : en
Publisher: IGI Global
Release Date : 2024-05-02
Advancing Software Engineering Through Ai Federated Learning And Large Language Models written by Sharma, Avinash Kumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-02 with Computers categories.
The rapid evolution of software engineering demands innovative approaches to meet the growing complexity and scale of modern software systems. Traditional methods often need help to keep pace with the demands for efficiency, reliability, and scalability. Manual development, testing, and maintenance processes are time-consuming and error-prone, leading to delays and increased costs. Additionally, integrating new technologies, such as AI, ML, Federated Learning, and Large Language Models (LLM), presents unique challenges in terms of implementation and ethical considerations. Advancing Software Engineering Through AI, Federated Learning, and Large Language Models provides a compelling solution by comprehensively exploring how AI, ML, Federated Learning, and LLM intersect with software engineering. By presenting real-world case studies, practical examples, and implementation guidelines, the book ensures that readers can readily apply these concepts in their software engineering projects. Researchers, academicians, practitioners, industrialists, and students will benefit from the interdisciplinary insights provided by experts in AI, ML, software engineering, and ethics.