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Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala
Unleash the power of PLCs by understanding and applying essential programming concepts such as structured text, programming logic, and technologies like ChatGPT Key Features Unleash the power of structured text by understanding its syntax, features, and applications Harness the power of programming logic and design by taking a design-first approach to PLC programming Leverage advanced concepts and technologies such as cybersecurity and generative AI with PLC Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionAs smart factories and advanced technology become more prevalent, the demand for PLC programmers with expertise beyond ladder logic is growing. This book introduces a new approach to PLC programming, preparing you for future challenges by exploring automation programming through computer science and text-based programming. The book begins by exploring the basic components of PLCs and how they integrate with other modules, giving you a clear understanding of system functionality. As you progress, you'll delve into PLC program execution, learning about flow and essential components for effective programming. Next, you'll understand program design with pseudocode and flowcharts, vital for planning programs. You'll then explore Boolean logic intricacies, harnessing logical functions and truth tables for precise control statements. Later, you'll delve into structured text, gaining a comprehensive grasp of syntax and features crucial for efficient programming. The journey continues with a focus on advanced topics like cybersecurity in PLC systems and leveraging generative AI (GenAI), such as ChatGPT, to enhance productivity. By the end of this book, you’ll be able to design real-world projects using pseudocode and flowcharts, and implement those designs in structured text.What you will learn Explore and understand how to implement PLC programs in structured text Experiment with common functions in structured text Control the flow of a PLC program with loop and conditional statements Discover how to design a PLC program with pseudocode and flowcharts Implement common sorting algorithms such as bubble sort and insertion sort, and understand concepts such as Big O Understand the basics of cybersecurity to protect PLC-based systems Leverage ChatGPT for PLC programming Understand the basics of troubleshooting hardware and fixing common problems Who this book is for This book is for automation engineering students and individuals seeking entry-level knowledge of PLC programming with structured text and other modern computer science concepts to excel in the advanced automation landscape. No prior knowledge of PLC programming is required.
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.
Design and use generative AI prompts that get helpful and practical results In The Quick Guide to Prompt Engineering, renowned technology futurist, management consultant, and AI thought leader Ian Khan delivers a practical and insightful discussion on taking the first steps in understanding and learning how to use generative AI. In this concise and quick start guide, you will learn how to design and use prompts to get the most out of Large Language Model generative AI applications like ChatGPT, DALL-E, Google’s Bard, and more. In the book, you’ll explore how to understand generative artificial intelligence and how to engineer prompts in a wide variety of industry use cases. You’ll also find thoughtful and illuminating case studies and hands-on exercises, as well as step-by-step guides, to get you up to speed on prompt engineering in no time at all. The book has been written for the non-technical user to take the first steps in the world of generative AI. Along with a helpful glossary of common terms, lists of useful additional reading and resources, and other resources, you’ll get: Explanations of the basics of generative artificial intelligence that help you to learn what’s going on under the hood of ChatGPT and other LLMs Stepwise guides to creating effective, efficient, and ethical prompts that help you get the most utility possible from these exciting new tools Strategies for generating text, images, video, voice, music, and other audio from various publicly available artificial intelligence tools Perfect for anyone with an interest in one of the newest and most practical technological advancements recently released to the public, The Quick Guide to Prompt Engineering is a must-read for tech enthusiasts, marketers, content creators, technical professionals, data experts, and anyone else expected to understand and use generative AI at work or at home. No previous experience is required.
In a world driven by data and powered by artificial intelligence, there's a superpower that's changing the game: Prompt Engineering. Join Diana Ashcroft, a seasoned data scientist and educator, on a journey through the dynamic landscape of prompt engineering in her latest book, Mastering Your Prompt Engineering Super Power. Prompt engineering is the key to unlocking the full potential of AI. In Mastering Your Prompt Engineering Super Power, Diana Ashcroft delves into the heart of this transformative field and reveals its immense significance. You'll discover how prompt engineering is reshaping industries, powering innovation, and shaping the future of society. Whether you're a seasoned AI professional or just starting your journey, Mastering Your Prompt Engineering Super Power is your guide to mastering prompt engineering. Diana takes complex concepts and distills them into practical, down-to-earth knowledge that anyone can grasp. You'll explore the realms of Natural Language Processing (NLP), Computer Vision, and more, gaining the skills needed to harness prompt engineering's incredible potential. Prompt engineering isn't just a buzzword; it's a force that's driving change in every sector. Diana provides real-world examples of how prompt engineering is making waves in industries like healthcare, finance, e-commerce, and beyond. You'll see how AI-powered prompts are enhancing productivity, improving customer experiences, and even revolutionizing education. Mastering Your Prompt Engineering Super Power isn't just a book; it's your passport to becoming a prompt engineering master. Diana guides you through hands-on techniques, tools, and frameworks used by professionals in the field. You'll learn to wield the power of AI-driven prompts to tackle complex tasks, from data preprocessing to model optimization. As we stand on the precipice of a new era, Diana Ashcroft illuminates the path forward. Discover how prompt engineering is shaping the future, from enabling smarter virtual assistants to aiding legal professionals in document analysis. The possibilities are endless, and Mastering Your Prompt Engineering Super Power equips you to seize them.
In the rapidly evolving landscape of artificial intelligence, few tools have captured the imagination and utility of both the public and professionals as effectively as ChatGPT. Developed by OpenAI, ChatGPT is a versatile conversational AI model that has proven to be a game-changer in various domains, from customer service to content creation, and from educational support to entertainment. However, unlocking the full potential of ChatGPT requires more than just a basic understanding of its capabilities; it demands a nuanced approach to crafting prompts that can elicit the most accurate, relevant, and creative responses. This book, "200 Prompt Engineering Tips for ChatGPT," is a comprehensive guide designed to elevate your interaction with this powerful AI tool. Whether you are a seasoned developer, a content creator, an educator, or simply an enthusiast eager to explore the depths of AI-driven conversation, this book will provide you with the insights and techniques needed to master prompt engineering. The Evolution of ChatGPT Since its inception, ChatGPT has undergone significant advancements. From its early versions to the sophisticated iterations we have today, each step in its evolution has expanded its capabilities and refined its conversational prowess. Understanding this evolution is crucial, as it highlights the increasing complexity and potential of the model, setting the stage for the advanced prompt engineering techniques that this book explores. Why Prompt Engineering Matters Prompt engineering is the art and science of designing inputs to maximize the quality and relevance of the outputs generated by an AI model. The effectiveness of ChatGPT hinges on the prompts it receives; well-crafted prompts can lead to responses that are not only accurate but also insightful and engaging. Conversely, poorly designed prompts can result in vague, irrelevant, or even misleading answers. This book aims to bridge the gap between the AI's potential and its practical application by providing you with 200 meticulously curated tips and strategies to enhance your prompt engineering skills. What You Will Learn Throughout this book, you will embark on a journey that covers the full spectrum of prompt engineering. We start with foundational concepts, ensuring that you have a solid grasp of the basics before moving on to more advanced techniques. Each tip is designed to be practical and actionable, with real-world examples and scenarios that demonstrate the application of these strategies in various contexts. Who This Book Is For "200 Prompt Engineering Tips for ChatGPT" is designed for a diverse audience. Whether you are a developer looking to integrate ChatGPT into your applications, a writer seeking to enhance your creative process, an educator aiming to leverage AI for teaching, or a business professional exploring new ways to engage with customers, this book offers valuable insights tailored to your needs. Welcome to "200 Prompt Engineering Tips for ChatGPT." Let's begin.
A Beginner's Guide to Large Language Models: Conversational AI for Non-Technical Enthusiasts Step into the revolutionary world of artificial intelligence with "A Beginner's Guide to Large Language Models: Conversational AI for Non-Technical Enthusiasts." Whether you're a curious individual or a professional seeking to leverage AI in your field, this book demystifies the complexities of large language models (LLMs) with engaging, easy-to-understand explanations and practical insights. Explore the fascinating journey of AI from its early roots to the cutting-edge advancements that power today's conversational AI systems. Discover how LLMs, like ChatGPT and Google's Gemini, are transforming industries, enhancing productivity, and sparking creativity across the globe. With the guidance of this comprehensive and accessible guide, you'll gain a solid understanding of how LLMs work, their real-world applications, and the ethical considerations they entail. Packed with vivid examples, hands-on exercises, and real-life scenarios, this book will empower you to harness the full potential of LLMs. Learn to generate creative content, translate languages in real-time, summarise complex information, and even develop AI-powered applications—all without needing a technical background. You'll also find valuable insights into the evolving job landscape, equipping you with the knowledge to pursue a successful career in this dynamic field. This guide ensures that AI is not just an abstract concept but a tangible tool you can use to transform your everyday life and work. Dive into the future with confidence and curiosity, and discover the incredible possibilities that large language models offer. Join the AI revolution and unlock the secrets of the technology that's reshaping our world. "A Beginner's Guide to Large Language Models" is your key to understanding and mastering the power of conversational AI. Introduction This introduction sets the stage for understanding the evolution of artificial intelligence (AI) and large language models (LLMs). It highlights the promise of making complex AI concepts accessible to non-technical readers and outlines the unique approach of this book. Chapter 1: Demystifying AI and LLMs: A Journey Through Time This chapter introduces the basics of AI, using simple analogies and real-world examples. It traces the evolution of AI, from rule-based systems to machine learning and deep learning, leading to the emergence of LLMs. Key concepts such as tokens, vocabulary, and embeddings are explained to build a solid foundation for understanding how LLMs process and generate language. Chapter 2: Mastering Large Language Models Delving deeper into the mechanics of LLMs, this chapter covers the transformer architecture, attention mechanisms, and the processes involved in training and fine-tuning LLMs. It includes hands-on exercises with prompts and discusses advanced techniques like chain-of-thought prompting and prompt chaining to optimise LLM performance. Chapter 3: The LLM Toolbox: Unleashing the Power of Language AI This chapter explores the diverse applications of LLMs in text generation, language translation, summarisation, question answering, and code generation. It also introduces multimodal LLMs that handle both text and images, showcasing their impact on various creative and professional fields. Practical examples and real-life scenarios illustrate how these tools can enhance productivity and creativity. Chapter 4: LLMs in the Real World: Transforming Industries Highlighting the transformative impact of LLMs across different industries, this chapter covers their role in healthcare, finance, education, creative industries, and business. It discusses how LLMs are revolutionising tasks such as medical diagnosis, fraud detection, personalised tutoring, and content creation, and explores the future of work in an AI-powered world. Chapter 5: The Dark Side of LLMs: Ethical Concerns and Challenges Addressing the ethical challenges of LLMs, this chapter covers bias and fairness, privacy concerns, misuse of LLMs, security threats, and the transparency of AI decision-making. It also discusses ethical frameworks for responsible AI development and presents diverse perspectives on the risks and benefits of LLMs. Chapter 6: Mastering LLMs: Advanced Techniques and Strategies This chapter focuses on advanced techniques for leveraging LLMs, such as combining transformers with other AI models, fine-tuning open-source LLMs for specific tasks, and building LLM-powered applications. It provides detailed guidance on prompt engineering for various applications and includes a step-by-step guide to creating an AI-powered chatbot. Chapter 7: LLMs and the Future: A Glimpse into Tomorrow Looking ahead, this chapter explores emerging trends and potential breakthroughs in AI and LLM research. It discusses ethical AI development, insights from leading AI experts, and visions of a future where LLMs are integrated into everyday life. The chapter highlights the importance of building responsible AI systems that address societal concerns. Chapter 8: Your LLM Career Roadmap: Navigating the AI Job Landscape Focusing on the growing demand for LLM expertise, this chapter outlines various career paths in the AI field, such as LLM scientists, engineers, and prompt engineers. It provides resources for building the necessary skillsets and discusses the evolving job market, emphasising the importance of continuous learning and adaptability in a rapidly changing industry. Thought-Provoking Questions, Simple Exercises, and Real-Life Scenarios The book concludes with practical exercises and real-life scenarios to help readers apply their knowledge of LLMs. It includes thought-provoking questions to deepen understanding and provides resources and tools for further exploration of LLM applications. Tools to Help with Your Exercises This section lists tools and platforms for engaging with LLM exercises, such as OpenAI's Playground, Google Translate, and various IDEs for coding. Links to these tools are provided to facilitate hands-on learning and experimentation.
This book provides a structured framework for exploring various aspects of prompt engineering for ChatGPT, from foundational principles to advanced techniques, real-world applications, and ethical considerations. It aims to guide readers in effectively harnessing the capabilities of ChatGPT through well-crafted prompts to achieve their goals. The digital age has ushered in a new era of communication, one where the boundaries between human and machine are becoming increasingly blurred. Artificial Intelligence (AI) technology, in its relentless evolution, has given rise to remarkable language models that can understand and generate human-like text. "Prompt Engineering for ChatGPT," demystifies the intricacies of this ground breaking technology, offering insights and strategies to harness its capabilities.
Have you ever wondered how technology could catapult you into a future where money flows with less effort? Or how Artificial Intelligence is redefining the rules of the game in the digital world? You'll discover the revolutionary strategies that are transforming the way people generate income online. Through a personal and moving journey, the author shares his own transformation and how ChatGPT not only improved his productivity, but also boosted his income in unimaginable ways. Within these pages, you will discover: Real success stories that will inspire you to take action. A detailed step-by-step approach to monetizing different areas of the digital world, from writing ebooks and creating online courses, to optimizing ad campaigns and 24/7 customer service. Practical Prompts that you can copy and paste to start making money immediately. A complete guide to the art of Prompt Engineering to maximize the potential of ChatGPT. This is not just another book about how to make money online. It's an invitation to transform your financial reality by harnessing the power of Artificial Intelligence.Whether you are a seasoned entrepreneur, a beginner in the digital world, or someone simply curious about the possibilities AI offers, this book is your master key to unlocking a world of opportunity. Take the leap. Discover how you can, with the right guidance and the right tool, generate Internet income smarter, not harder. The future is here, and it's waiting for you!
Large language models (LLMs) and diffusion models such as ChatGPT and Stable Diffusion have unprecedented potential. Because they have been trained on all the public text and images on the internet, they can make useful contributions to a wide variety of tasks. And with the barrier to entry greatly reduced today, practically any developer can harness LLMs and diffusion models to tackle problems previously unsuitable for automation. With this book, you'll gain a solid foundation in generative AI, including how to apply these models in practice. When first integrating LLMs and diffusion models into their workflows, most developers struggle to coax reliable enough results from them to use in automated systems. Authors James Phoenix and Mike Taylor show you how a set of principles called prompt engineering can enable you to work effectively with AI. Learn how to empower AI to work for you. This book explains: The structure of the interaction chain of your program's AI model and the fine-grained steps in between How AI model requests arise from transforming the application problem into a document completion problem in the model training domain The influence of LLM and diffusion model architecture—and how to best interact with it How these principles apply in practice in the domains of natural language processing, text and image generation, and code