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As ChatGPT becomes more popular, people are paying more attention to the potential and applications of large language models. Prompt engineering, which involves designing precise input instructions to guide the model to produce the desired output, is crucial for how to use AI large language models in the new era. In this book, we delve into the widespread use of large language models such as GPT and ChatGPT in various application areas and how to maximize their potential through carefully designed prompts. This book aims to reveal the core principles of AI prompt engineering and show readers how to optimize models and meet specific scenario needs through practical cases and experiments.Whether you are a model developer, a large language model user or an AI enthusiast, this book will provide you with valuable insights and practical advice to help you better utilize large language models and explore the infinite possibilities of AI prompt engineering. For model users and enthusiasts, this book will provide knowledge on prompt design basics, strategies, advanced techniques and practical application cases to help you use models more effectively in different scenarios. For model developers, this book will introduce the principles, training methods, limitations and custom fine-tuning of large language models to help you better understand how models work and make wiser decisions when designing and optimizing models. At the same time, this book will also explore some specific strategies for following ethical norms, avoiding bias and discrimination when using large language models.
This eBook ‘Prompt Engineering for Large Language Models’ is meant to be a concise and practical guide for the reader. It teaches you to write better prompts for generative artificial intelligence models like Google’s BARD and OpenAI’s ChatGPT. These models have been trained on huge volumes of data to generate text and provide a free of cost, web-based interface to the underlying models as of 11 Nov. 2023. These models are fine tuned for conversational AI applications. All the prompts used in the eBook have been tested on the web interface of BARD and ChatGPT-3.5.
Delve into the intricate world of Prompt Engineering, the fine art of crafting communication to unlock the full potential of AI interactions. This comprehensive guide is a valuable resource for AI enthusiasts, developers, content creators, or anyone curious about AI. Within the pages of this guide, you'll find the keys to crafting prompts that evoke engaging, relevant, and accurate responses from AI. This isn't just about creating commands, but understanding the AI's 'rhythm', predicting its responses, and adapting your prompts to improve performance. Think of it as a dance with AI, where both you and the AI learn, adapt, and improvise to produce the most harmonious results. Filled with practical insights, techniques, and real-world examples, this guidebook covers various topics. Learn to craft effective prompts, fine-tune AI for optimal responses, manage ambiguity in language, and develop an intuitive connection with the AI. All these aspects are integral to becoming proficient at Prompt Engineering. This book goes beyond just an informative guide; it invites you into the fascinating dance of human-AI interaction. It aims to turn the AI interaction from a monologue into a dialogue, from a mechanical exchange into a harmonious dance. Begin your journey and learn to lead the dance with AI!
A Comprehensive Guide to Leverage Generative AI in the Modern Enterprise KEY FEATURES ● Gain a comprehensive understanding of LLMs within the framework of Generative AI, from foundational concepts to advanced applications. ● Dive into practical exercises and real-world applications, accompanied by detailed code walkthroughs in Python. ● Explore LLMOps with a dedicated focus on ensuring trustworthy AI and best practices for deploying, managing, and maintaining LLMs in enterprise settings. ● Prioritize the ethical and responsible use of LLMs, with an emphasis on building models that adhere to principles of fairness, transparency, and accountability, fostering trust in AI technologies. DESCRIPTION “Mastering Large Language Models with Python” is an indispensable resource that offers a comprehensive exploration of Large Language Models (LLMs), providing the essential knowledge to leverage these transformative AI models effectively. From unraveling the intricacies of LLM architecture to practical applications like code generation and AI-driven recommendation systems, readers will gain valuable insights into implementing LLMs in diverse projects. Covering both open-source and proprietary LLMs, the book delves into foundational concepts and advanced techniques, empowering professionals to harness the full potential of these models. Detailed discussions on quantization techniques for efficient deployment, operational strategies with LLMOps, and ethical considerations ensure a well-rounded understanding of LLM implementation. Through real-world case studies, code snippets, and practical examples, readers will navigate the complexities of LLMs with confidence, paving the way for innovative solutions and organizational growth. Whether you seek to deepen your understanding, drive impactful applications, or lead AI-driven initiatives, this book equips you with the tools and insights needed to excel in the dynamic landscape of artificial intelligence. WHAT WILL YOU LEARN ● In-depth study of LLM architecture and its versatile applications across industries. ● Harness open-source and proprietary LLMs to craft innovative solutions. ● Implement LLM APIs for a wide range of tasks spanning natural language processing, audio analysis, and visual recognition. ● Optimize LLM deployment through techniques such as quantization and operational strategies like LLMOps, ensuring efficient and scalable model usage. ● Master prompt engineering techniques to fine-tune LLM outputs, enhancing quality and relevance for diverse use cases. ● Navigate the complex landscape of ethical AI development, prioritizing responsible practices to drive impactful technology adoption and advancement. WHO IS THIS BOOK FOR? This book is tailored for software engineers, data scientists, AI researchers, and technology leaders with a foundational understanding of machine learning concepts and programming. It's ideal for those looking to deepen their knowledge of Large Language Models and their practical applications in the field of AI. If you aim to explore LLMs extensively for implementing inventive solutions or spearheading AI-driven projects, this book is tailored to your needs. TABLE OF CONTENTS 1. The Basics of Large Language Models and Their Applications 2. Demystifying Open-Source Large Language Models 3. Closed-Source Large Language Models 4. LLM APIs for Various Large Language Model Tasks 5. Integrating Cohere API in Google Sheets 6. Dynamic Movie Recommendation Engine Using LLMs 7. Document-and Web-based QA Bots with Large Language Models 8. LLM Quantization Techniques and Implementation 9. Fine-tuning and Evaluation of LLMs 10. Recipes for Fine-Tuning and Evaluating LLMs 11. LLMOps - Operationalizing LLMs at Scale 12. Implementing LLMOps in Practice Using MLflow on Databricks 13. Mastering the Art of Prompt Engineering 14. Prompt Engineering Essentials and Design Patterns 15. Ethical Considerations and Regulatory Frameworks for LLMs 16. Towards Trustworthy Generative AI (A Novel Framework Inspired by Symbolic Reasoning) Index
Mastering Prompt Engineering: Unlocking the Power of Language Models is your comprehensive guide to harnessing the full potential of advanced language models like GPT-4, BERT, and T5. This book dives into the art and science of prompt engineering, providing readers with the tools and techniques needed to craft precise and effective prompts that drive optimal performance from these powerful AI models. Starting with the fundamentals, you'll explore what prompt engineering is, why it is crucial, and how it can be applied across various domains, from chatbots and content generation to sentiment analysis and code generation. The book offers a detailed overview of popular LLMs, highlighting their unique capabilities and differences in prompt design. You'll learn key concepts and terminology essential for understanding LLMs, along with basic principles for creating clear, specific, and contextually relevant prompts. With practical examples and case studies, the book illustrates the impact of good and bad prompts, helping you refine your approach. Advanced techniques are covered extensively, including dynamic prompt generation, conditional and contextual prompts, and strategies for zero-shot and few-shot learning. Optimization strategies, feedback incorporation, and iterative refinement are emphasized to ensure continuous improvement in prompt design. Specialized use cases are addressed, showcasing how prompt engineering can enhance chatbots, content summarization, sentiment analysis, question answering, programming assistance, and personalized recommendations. The book also explores the tools and frameworks available for prompt engineering, such as OpenAI's API and Hugging Face Transformers, with sample code to get you started. Metrics for prompt evaluation, A/B testing, and user feedback integration are discussed to help you measure and enhance prompt performance effectively. Additionally, the book delves into common challenges, ethical considerations, and best practices to ensure robust and scalable prompt designs. Finally, future trends in prompt engineering are explored, preparing you for emerging technologies and innovations in interactive AI. Mastering Prompt Engineering is an essential resource for anyone looking to leverage the power of language models in their applications and projects.
Class-tested and coherent, this textbook teaches classical and web information retrieval, including web search and the related areas of text classification and text clustering from basic concepts. It gives an up-to-date treatment of all aspects of the design and implementation of systems for gathering, indexing, and searching documents; methods for evaluating systems; and an introduction to the use of machine learning methods on text collections. All the important ideas are explained using examples and figures, making it perfect for introductory courses in information retrieval for advanced undergraduates and graduate students in computer science. Based on feedback from extensive classroom experience, the book has been carefully structured in order to make teaching more natural and effective. Slides and additional exercises (with solutions for lecturers) are also available through the book's supporting website to help course instructors prepare their lectures.
"This eBook features 501 sample writing prompts that are designed to help you improve your writing and gain the necessary writing skills needed to ace essay exams. Build your essay-writing confidence fast with 501 Writing Prompts!" --
What do we mean by the word ‘context’ in education and how does our context influence the way that we learn? What role can technology play in enhancing learning and what is the future of technology within learning? Re-Designing Learning Contexts seeks to re-dress the lack of attention that has traditionally been paid to a learner’s wider context and proposes a model to help educators and technologists develop more productive learning contexts. It defines context as the interactions between the learner and a set of inter-related resource elements that are not tied to a physical or virtual location. Context is something that belongs to an individual and that is created through their interactions in the world. Based on original, empirical research, the book considers the intersection between learning, context and technology, and explores: the meaning of the concept of context and it’s relationship to learning the ways in which different types of technology can scaffold learning in context the Learner-Centric ‘Ecology of Resources’ model of context as a framework for designing technology-rich learning environments the importance of matching available resources to each learner’s particular needs the ways in which the learner’s environment and the technologies available might change over the coming years the potential impact of recent technological developments within computer science and artificial intelligence. This interdisciplinary study draws on a range of disciplines, including geography, anthropology, psychology, education and computing, to investigate the dynamics and potential of teacher-learner interaction within a learning continuum, and across a variety of locations. It will be of interest to those teaching, researching and thinking about the use of technology in learning and pedagogy, as well as those involved in developing technology for education and those who use it in their own teaching. For practical examples of the way the Ecology of Resources framework has been used visit: http://eorframework.pbworks.com.
Listen to people in every field and you'll hear a call for more sophisticated leadership—for leaders who can solve more complex problems than the human race has ever faced. But these leaders won't simply come to the fore; we have to develop them, and we must cultivate them as quickly as is humanly possible. Changing on the Job is a means to this end. As opposed to showing readers how to play the role of a leader in a "paint by numbers" fashion, Changing on the Job builds on theories of adult growth and development to help readers become more thoughtful individuals, capable of leading in any scenario. Moving from the theoretical to the practical, and employing real-world examples, author Jennifer Garvey Berger offers a set of building blocks to help cultivate an agile workforce while improving performance. Coaches, HR professionals, thoughtful leaders, and anyone who wants to flourish on the job will find this book a vital resource for developing their own capacities and those of the talent that they support.
Revised and Updated, Featuring a New Case Study How do successful companies create products people can’t put down? Why do some products capture widespread attention while others flop? What makes us engage with certain products out of sheer habit? Is there a pattern underlying how technologies hook us? Nir Eyal answers these questions (and many more) by explaining the Hook Model—a four-step process embedded into the products of many successful companies to subtly encourage customer behavior. Through consecutive “hook cycles,” these products reach their ultimate goal of bringing users back again and again without depending on costly advertising or aggressive messaging. Hooked is based on Eyal’s years of research, consulting, and practical experience. He wrote the book he wished had been available to him as a start-up founder—not abstract theory, but a how-to guide for building better products. Hooked is written for product managers, designers, marketers, start-up founders, and anyone who seeks to understand how products influence our behavior. Eyal provides readers with: • Practical insights to create user habits that stick. • Actionable steps for building products people love. • Fascinating examples from the iPhone to Twitter, Pinterest to the Bible App, and many other habit-forming products.