AI Foundations of Prompt Engineering
AI Foundations of Prompt Engineering

Author: Jon Adams

Publisher: Green Mountain Computing

Published:

Total Pages: 167

ISBN-13:

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Unlock the secrets of effective communication with AI through "AI Foundations of Prompt Engineering," a comprehensive guide that delves into the nuanced art of prompt engineering. Authored with the intent to demystify the process of crafting prompts that elicit desired responses from AI, this book serves as both an introduction for newcomers and a deep dive for seasoned professionals in the field of artificial intelligence. Book Contents: Chapter 1: Defining Prompt Engineering - Introduction to the concept and importance of prompt engineering in AI interactions. Chapter 2: Elements of a Good Prompt - Exploration of the critical components that constitute an effective prompt. Chapter 3: Word Choice in Prompts - Insights into the significance of choosing the right words for clarity and impact. Chapter 4: Crafting Questions for AI - Guidelines for formulating questions that AI can understand and respond to accurately. Chapter 5: Sentence Structure in AI Prompts - Examination of how sentence structure affects AI's comprehension and responses. Chapter 6: Avoiding Ambiguity - Strategies for creating clear and unambiguous prompts to ensure precise AI responses. Chapter 7: Contextual Considerations - Discussion on the role of context in enhancing the effectiveness of prompts. Chapter 8: Testing and Iterating Prompts - Methods for testing prompts and refining them based on feedback. Chapter 9: Advanced Prompt Engineering - Advanced techniques and considerations for expert-level prompt engineering. Why This Book? Practical Approach: Unlike purely theoretical texts, this book offers concrete guidance, practical examples, and exercises for real-world application. Comprehensive Coverage: From foundational concepts to advanced techniques, this book covers the entire spectrum of prompt engineering. Expert Insights: Benefit from the author's deep understanding of AI dialogue design, informed by the latest research and practices in the field. Whether you're just starting out or seeking to enhance your skills in AI communication, "AI Foundations of Prompt Engineering" is an essential resource that will equip you with the knowledge and tools to master the art of prompt engineering. Embark on this educational journey and unlock the potential of AI through expertly crafted prompts.

Generative AI Foundations in Python
Generative AI Foundations in Python

Author: Carlos Rodriguez

Publisher: Packt Publishing Ltd

Published: 2024-07-26

Total Pages: 190

ISBN-13: 1835464912

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Begin your generative AI journey with Python as you explore large language models, understand responsible generative AI practices, and apply your knowledge to real-world applications through guided tutorials Key Features Gain expertise in prompt engineering, LLM fine-tuning, and domain adaptation Use transformers-based LLMs and diffusion models to implement AI applications Discover strategies to optimize model performance, address ethical considerations, and build trust in AI systems Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe intricacies and breadth of generative AI (GenAI) and large language models can sometimes eclipse their practical application. It is pivotal to understand the foundational concepts needed to implement generative AI. This guide explains the core concepts behind -of-the-art generative models by combining theory and hands-on application. Generative AI Foundations in Python begins by laying a foundational understanding, presenting the fundamentals of generative LLMs and their historical evolution, while also setting the stage for deeper exploration. You’ll also understand how to apply generative LLMs in real-world applications. The book cuts through the complexity and offers actionable guidance on deploying and fine-tuning pre-trained language models with Python. Later, you’ll delve into topics such as task-specific fine-tuning, domain adaptation, prompt engineering, quantitative evaluation, and responsible AI, focusing on how to effectively and responsibly use generative LLMs. By the end of this book, you’ll be well-versed in applying generative AI capabilities to real-world problems, confidently navigating its enormous potential ethically and responsibly.What you will learn Discover the fundamentals of GenAI and its foundations in NLP Dissect foundational generative architectures including GANs, transformers, and diffusion models Find out how to fine-tune LLMs for specific NLP tasks Understand transfer learning and fine-tuning to facilitate domain adaptation, including fields such as finance Explore prompt engineering, including in-context learning, templatization, and rationalization through chain-of-thought and RAG Implement responsible practices with generative LLMs to minimize bias, toxicity, and other harmful outputs Who this book is for This book is for developers, data scientists, and machine learning engineers embarking on projects driven by generative AI. A general understanding of machine learning and deep learning, as well as some proficiency with Python, is expected.

Deep Learning for Coders with fastai and PyTorch
Deep Learning for Coders with fastai and PyTorch

Author: Jeremy Howard

Publisher: O'Reilly Media

Published: 2020-06-29

Total Pages: 624

ISBN-13: 1492045497

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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

AI Essentials & Fundamentals exam preparation
AI Essentials & Fundamentals exam preparation

Author: Gitte Snoeren

Publisher: Van Haren

Published: 2024-09-16

Total Pages: 233

ISBN-13: 9401812403

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This exam preparation booklet is a comprehensive guide designed to help you earn your certification for the NL AIC AI Fundamentals (AI Brevet) and AI Basis. It can also be used for exams based on the EXIN BCS Artificial Intelligence Essentials and/or Foundation. For those focusing on the Artificial Intelligence Essentials, sections 1.1 and 2.1 are relevant, while all sections apply to the Artificial Intelligence Foundation. All the knowledge areas described in the preparation guide will be covered with exam-like questions. The number of questions per topic can differ, depending on the weights used in the formal exam requirements. The booklet is structured into two main sections: The first part features questions without answers, allowing you to test your knowledge and identify areas for improvement. The second part provides the correct answers along with concise explanations to enhance your understanding. This exam preparation booklet will help prepare you for various acknowledges AI certification exams and provides you with sertanty going in to the exam session.

Microsoft Azure AI Fundamentals AI-900 Exam Guide
Microsoft Azure AI Fundamentals AI-900 Exam Guide

Author: Aaron Guilmette

Publisher: Packt Publishing Ltd

Published: 2024-05-31

Total Pages: 288

ISBN-13: 1835885675

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Get ready to pass the certification exam on your first attempt by gaining actionable insights into AI concepts, ML techniques, and Azure AI services covered in the latest AI-900 exam syllabus from two industry experts Key Features Discover Azure AI services, including computer vision, Auto ML, NLP, and OpenAI Explore AI use cases, such as image identification, chatbots, and more Work through 145 practice questions under chapter-end self-assessments and mock exams Purchase of this book unlocks access to web-based exam prep resources, including mock exams, flashcards, and exam tips Book Description The AI-900 exam helps you take your first step into an AI-shaped future. Regardless of your technical background, this book will help you test your understanding of the key AI-related topics and tools used to develop AI solutions in Azure cloud. This exam guide focuses on AI workloads, including natural language processing (NLP) and large language models (LLMs). You'll explore Microsoft's responsible AI principles like safety and accountability. Then, you'll cover the basics of machine learning (ML), including classification and deep learning, and learn how to use training and validation datasets with Azure ML. Using Azure AI Vision, face detection, and Video Indexer services, you'll get up to speed with computer vision-related topics like image classification, object detection, and facial detection. Later chapters cover NLP features such as key phrase extraction, sentiment analysis, and speech processing using Azure AI Language, speech, and translator services. The book also guides you through identifying GenAI models and leveraging Azure OpenAI Service for content generation. At the end of each chapter, you'll find chapter review questions with answers, provided as an online resource. By the end of this exam guide, you'll be able to work with AI solutions in Azure and pass the AI-900 exam using the online exam prep resources. What you will learn Discover various types of artificial intelligence (AI)workloads and services in Azure Cover Microsoft's guiding principles for responsible AI development and use Understand the fundamental principles of how AI and machine learning work Explore how AI models can recognize content in images and documents Gain insights into the features and use cases for natural language processing Explore the capabilities of generative AI services Who this book is for Whether you're a cloud engineer, software developer, an aspiring data scientist, or simply interested in learning AI/ML concepts and capabilities on Azure, this book is for you. The book also serves as a foundation for those looking to attempt more advanced AI and data science-related certification exams (e.g. Microsoft Certified: Azure AI Engineer Associate). Although no experience in data science and software engineering is required, basic knowledge of cloud concepts and client-server applications is assumed.

Text Generative AI courseware
Text Generative AI courseware

Author: Fabienne Mouris

Publisher: Van Haren

Published: 2023-10-20

Total Pages: 105

ISBN-13: 9401810869

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The course is mainly practical (applying generative AI/prompt-engineering), in action activities where you make prompts and learn best practices on Text Generative AI, while doing. Gain a comprehensive understanding of Text Generative AI and its capabilities Develop critical thinking skills to evaluate the potential of Text Generative AI in different business use cases Understanding of the architecture behind the model Master the skill of prompt engineering for effective interaction with Text Generative AI Learn how to integrate Text Generative AI into existing workflows Understand the limitations and risks associated with Text Generative AI Individuals who need a basic understanding Text Generative AI Professionals who want to learn the potential and pitfalls of Text Generative AI and how to deal with it Business Analyst. The course is mainly practical, with interactive activities where you make prompts and learn by doing. You will also get feedback and guidance from experienced instructors and peers. By the end of the course, you will be able to: Gain a comprehensive understanding of Text Generative AI and its capabilities Develop critical thinking skills to evaluate the potential of Text Generative AI in different business use cases Master the skill of prompt engineering for effective interaction with Text Generative AI Learn how to integrate Text Generative AI into existing workflows Understand the limitations and risks associated with Text Generative AI The course is suitable for anyone who needs a basic understanding of Text Generative AI, such as: Professionals who want to learn the potential and pitfalls of Text Generative AI and how to deal with them Business analysts, marketers, content creators, educators, researchers, and other roles that can benefit from using Text Generative AI Students who want to explore the field of Text Generative AI and its applications The course prepares you for the EDF Certified (Text) Generative AI Ambassador exam, which is a certification program offered by the Effective Data Foundation (EDF) and Van Haren Certify. By passing this exam, you will become a certified Text Generative AI Ambassador and gain a competitive edge in your field.

Unlocking the Secrets of Prompt Engineering
Unlocking the Secrets of Prompt Engineering

Author: Gilbert Mizrahi

Publisher: Packt Publishing Ltd

Published: 2024-01-12

Total Pages: 316

ISBN-13: 1835088260

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Enhance your writing with AI by mastering prompt engineering techniques and become an expert in developing and utilizing LLM prompts across applications Key Features Master prompt engineering techniques to harness AI's writing potential Discover diverse LLM applications for content creation and beyond Learn through practical examples, use cases, and hands-on guidance Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionUnlocking the Secrets of Prompt Engineering is your key to mastering the art of AI-driven writing. This book propels you into the world of large language models (LLMs), empowering you to create and apply prompts effectively for diverse applications, from revolutionizing content creation and chatbots to coding assistance. Starting with the fundamentals of prompt engineering, this guide provides a solid foundation in LLM prompts, their components, and applications. Through practical examples and use cases, you'll discover how LLMs can be used for generating product descriptions, personalized emails, social media posts, and even creative writing projects like fiction and poetry. The book covers advanced use cases such as creating and promoting podcasts, integrating LLMs with other tools, and using AI for chatbot development. But that’s not all. You'll also delve into the ethical considerations, best practices, and limitations of using LLM prompts as you experiment and optimize your approach for best results. By the end of this book, you'll have unlocked the full potential of AI in writing and content creation to generate ideas, overcome writer's block, boost productivity, and improve communication skills.What you will learn Explore the different types of prompts, their strengths, and weaknesses Understand the AI agent's knowledge and mental model Enhance your creative writing with AI insights for fiction and poetry Develop advanced skills in AI chatbot creation and deployment Discover how AI will transform industries such as education, legal, and others Integrate LLMs with various tools to boost productivity Understand AI ethics and best practices, and navigate limitations effectively Experiment and optimize AI techniques for best results Who this book is for This book is for a wide audience, including writers, marketing and business professionals, researchers, students, tech enthusiasts, and creative individuals. Anyone looking for strategies and examples for using AI co-writing tools like ChatGPT effectively in domains such as content creation, drafting emails, and inspiring artistic works, will find this book especially useful. If you are interested in AI, NLP, and innovative software for personal or professional use, this is the book for you.

Prompt Engineering Using ChatGPT
Prompt Engineering Using ChatGPT

Author: Mehrzad Tabatabaian

Publisher: Walter de Gruyter GmbH & Co KG

Published: 2024-06-17

Total Pages: 142

ISBN-13: 1501518895

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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.

Generative AI on AWS
Generative AI on AWS

Author: Chris Fregly

Publisher: "O'Reilly Media, Inc."

Published: 2023-11-13

Total Pages: 312

ISBN-13: 1098159195

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Companies today are moving rapidly to integrate generative AI into their products and services. But there's a great deal of hype (and misunderstanding) about the impact and promise of this technology. With this book, Chris Fregly, Antje Barth, and Shelbee Eigenbrode from AWS help CTOs, ML practitioners, application developers, business analysts, data engineers, and data scientists find practical ways to use this exciting new technology. You'll learn the generative AI project life cycle including use case definition, model selection, model fine-tuning, retrieval-augmented generation, reinforcement learning from human feedback, and model quantization, optimization, and deployment. And you'll explore different types of models including large language models (LLMs) and multimodal models such as Stable Diffusion for generating images and Flamingo/IDEFICS for answering questions about images. Apply generative AI to your business use cases Determine which generative AI models are best suited to your task Perform prompt engineering and in-context learning Fine-tune generative AI models on your datasets with low-rank adaptation (LoRA) Align generative AI models to human values with reinforcement learning from human feedback (RLHF) Augment your model with retrieval-augmented generation (RAG) Explore libraries such as LangChain and ReAct to develop agents and actions Build generative AI applications with Amazon Bedrock