Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Prompt Engineering For Large Language Models
Download Prompt Engineering For Large Language Models full books in PDF, epub, and Kindle. Read online Prompt Engineering For Large Language Models ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Prompt Engineering for Large Language Models by : Nimrita Koul
Download or read book Prompt Engineering for Large Language Models written by Nimrita Koul and published by Nimrita Koul. This book was released on with total page 151 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Prompt Engineering: Unleashing the Infinite Potential of Large Language Models by : shisong wu
Download or read book Prompt Engineering: Unleashing the Infinite Potential of Large Language Models written by shisong wu and published by . This book was released on 2023-05-16 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Advanced Prompt Engineering by : Tejaswini Bodake
Download or read book Advanced Prompt Engineering written by Tejaswini Bodake and published by Pencil. This book was released on 2024-05-17 with total page 43 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Advanced Prompt Engineering" is your definitive guide to mastering the art and science of prompt engineering in natural language processing. From fine-tuning language models to crafting precise prompts, this book equips you with the knowledge and techniques needed to harness the full potential of language models. Dive deep into advanced concepts such as controlling model outputs, optimizing prompts for specific tasks, and collaborating effectively with subject matter experts. With practical examples, case studies, and hands-on exercises, this comprehensive resource empowers you to elevate your prompt engineering skills and revolutionize the way you interact with language models. Whether you're a seasoned practitioner or a newcomer to the field.
Book Synopsis Prompt Engineering for Llms by : John Berryman
Download or read book Prompt Engineering for Llms written by John Berryman and published by . This book was released on 2025-01-28 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Large language models (LLMs) promise unprecedented benefits. Well versed in common topics of human discourse, LLMs can make useful contributions to a large variety of tasks, especially now that the barrier for interacting with them has been greatly reduced. Potentially, any developer can harness the power of LLMs to tackle large classes of problems previously beyond the reach of automation. This book provides a solid foundation of LLM principles and explains how to apply them in practice. When first integrating LLMs into workflows, most developers struggle to coax useful insights from them. That's because communicating with AI is different from communicating with humans. This guide shows you how to present your problem in the model-friendly way called prompt engineering. With this book, you'll: Examine the user-program-AI-user model interaction loop Understand the influence of LLM architecture and learn how to best interact with it Design a complete prompt crafting strategy for an application that fits into the application context Gather and triage context elements to make an efficient prompt Formulate those elements so that the model processes them in the way that's desired Master specific prompt crafting techniques including few-shot learning, and chain-of-thought prompting
Book Synopsis The Quick Guide to Prompt Engineering by : Ian Khan
Download or read book The Quick Guide to Prompt Engineering written by Ian Khan and published by John Wiley & Sons. This book was released on 2024-03-26 with total page 485 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Demystifying Large Language Models by : James Chen
Download or read book Demystifying Large Language Models written by James Chen and published by James Chen. This book was released on 2024-04-25 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a comprehensive guide aiming to demystify the world of transformers -- the architecture that powers Large Language Models (LLMs) like GPT and BERT. From PyTorch basics and mathematical foundations to implementing a Transformer from scratch, you'll gain a deep understanding of the inner workings of these models. That's just the beginning. Get ready to dive into the realm of pre-training your own Transformer from scratch, unlocking the power of transfer learning to fine-tune LLMs for your specific use cases, exploring advanced techniques like PEFT (Prompting for Efficient Fine-Tuning) and LoRA (Low-Rank Adaptation) for fine-tuning, as well as RLHF (Reinforcement Learning with Human Feedback) for detoxifying LLMs to make them aligned with human values and ethical norms. Step into the deployment of LLMs, delivering these state-of-the-art language models into the real-world, whether integrating them into cloud platforms or optimizing them for edge devices, this section ensures you're equipped with the know-how to bring your AI solutions to life. Whether you're a seasoned AI practitioner, a data scientist, or a curious developer eager to advance your knowledge on the powerful LLMs, this book is your ultimate guide to mastering these cutting-edge models. By translating convoluted concepts into understandable explanations and offering a practical hands-on approach, this treasure trove of knowledge is invaluable to both aspiring beginners and seasoned professionals. Table of Contents 1. INTRODUCTION 1.1 What is AI, ML, DL, Generative AI and Large Language Model 1.2 Lifecycle of Large Language Models 1.3 Whom This Book Is For 1.4 How This Book Is Organized 1.5 Source Code and Resources 2. PYTORCH BASICS AND MATH FUNDAMENTALS 2.1 Tensor and Vector 2.2 Tensor and Matrix 2.3 Dot Product 2.4 Softmax 2.5 Cross Entropy 2.6 GPU Support 2.7 Linear Transformation 2.8 Embedding 2.9 Neural Network 2.10 Bigram and N-gram Models 2.11 Greedy, Random Sampling and Beam 2.12 Rank of Matrices 2.13 Singular Value Decomposition (SVD) 2.14 Conclusion 3. TRANSFORMER 3.1 Dataset and Tokenization 3.2 Embedding 3.3 Positional Encoding 3.4 Layer Normalization 3.5 Feed Forward 3.6 Scaled Dot-Product Attention 3.7 Mask 3.8 Multi-Head Attention 3.9 Encoder Layer and Encoder 3.10 Decoder Layer and Decoder 3.11 Transformer 3.12 Training 3.13 Inference 3.14 Conclusion 4. PRE-TRAINING 4.1 Machine Translation 4.2 Dataset and Tokenization 4.3 Load Data in Batch 4.4 Pre-Training nn.Transformer Model 4.5 Inference 4.6 Popular Large Language Models 4.7 Computational Resources 4.8 Prompt Engineering and In-context Learning (ICL) 4.9 Prompt Engineering on FLAN-T5 4.10 Pipelines 4.11 Conclusion 5. FINE-TUNING 5.1 Fine-Tuning 5.2 Parameter Efficient Fine-tuning (PEFT) 5.3 Low-Rank Adaptation (LoRA) 5.4 Adapter 5.5 Prompt Tuning 5.6 Evaluation 5.7 Reinforcement Learning 5.8 Reinforcement Learning Human Feedback (RLHF) 5.9 Implementation of RLHF 5.10 Conclusion 6. DEPLOYMENT OF LLMS 6.1 Challenges and Considerations 6.2 Pre-Deployment Optimization 6.3 Security and Privacy 6.4 Deployment Architectures 6.5 Scalability and Load Balancing 6.6 Compliance and Ethics Review 6.7 Model Versioning and Updates 6.8 LLM-Powered Applications 6.9 Vector Database 6.10 LangChain 6.11 Chatbot, Example of LLM-Powered Application 6.12 WebUI, Example of LLM-Power Application 6.13 Future Trends and Challenges 6.14 Conclusion REFERENCES ABOUT THE AUTHOR
Book Synopsis LLM Prompt Engineering for Developers by : Aymen El Amri
Download or read book LLM Prompt Engineering for Developers written by Aymen El Amri and published by Packt Publishing Ltd. This book was released on 2024-05-23 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explore the dynamic field of LLM prompt engineering with this book. Starting with fundamental NLP principles & progressing to sophisticated prompt engineering methods, this book serves as the perfect comprehensive guide. Key Features In-depth coverage of prompt engineering from basics to advanced techniques. Insights into cutting-edge methods like AutoCoT and transfer learning. Comprehensive resource sections including prompt databases and tools. Book Description"LLM Prompt Engineering For Developers" begins by laying the groundwork with essential principles of natural language processing (NLP), setting the stage for more complex topics. It methodically guides readers through the initial steps of understanding how large language models work, providing a solid foundation that prepares them for the more intricate aspects of prompt engineering. As you proceed, the book transitions into advanced strategies and techniques that reveal how to effectively interact with and utilize these powerful models. From crafting precise prompts that enhance model responses to exploring innovative methods like few-shot and zero-shot learning, this resource is designed to unlock the full potential of language model technology. This book not only teaches the technical skills needed to excel in the field but also addresses the broader implications of AI technology. It encourages thoughtful consideration of ethical issues and the impact of AI on society. By the end of this book, readers will master the technical aspects of prompt engineering & appreciate the importance of responsible AI development, making them well-rounded professionals ready to focus on the advancement of this cutting-edge technology.What you will learn Understand the principles of NLP and their application in LLMs. Set up and configure environments for developing with LLMs. Implement few-shot and zero-shot learning techniques. Enhance LLM outputs through AutoCoT and self-consistency methods. Apply transfer learning to adapt LLMs to new domains. Develop practical skills in testing & scoring prompt effectiveness. Who this book is for The target audience for "LLM Prompt Engineering For Developers" includes software developers, AI enthusiasts, technical team leads, advanced computer science students, and AI researchers with a basic understanding of artificial intelligence. Ideal for those looking to deepen their expertise in large language models and prompt engineering, this book serves as a practical guide for integrating advanced AI-driven projects and research into various workflows, assuming some foundational programming knowledge and familiarity with AI concepts.
Book Synopsis The Prompt Engineer's Handbook: Effective Prompts for Optimal Results by : Alexander Schmidt
Download or read book The Prompt Engineer's Handbook: Effective Prompts for Optimal Results written by Alexander Schmidt and published by epubli. This book was released on 2024-05-24 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Art of Prompt Engineering: Discover the transformative potential of AI systems. Artificial Intelligence is revolutionising the way we communicate and work. To fully harness the capabilities of AI systems like ChatGPT or Claude one must master the art of formulating precise and creative prompts. Prompt Engineering is essential for obtaining customised, high-quality results from AI. In this book, Alexander Schmidt, an experienced lecturer and expert in analytics and AI-powered communication, guides you through the world of Prompt Engineering step-by-step. Learn the basics, create effective Basic Prompts, and master advanced techniques such as Mega Prompts. Explore how to adapt prompts to various use cases, navigate common pitfalls, and maximise the use of language models like GPT-4. Packed with practical examples, reflective questions, and checklists, this book equips you to sharpen your Prompt Engineering skills in a focused manner. Whether in marketing, data analysis, or customer service, after reading this book, you will be well-prepared to effectively deploy AI systems in your daily work, boosting your productivity and creativity to new heights. Dive into the fascinating world of Prompt Engineering and unlock the vast opportunities that Artificial Intelligence offers for enhancing communication and collaboration. With this guide, you possess the essential tools to precisely control AI systems and achieve impressive results.
Book Synopsis A Short and Practical Textbook of Prompt Engineering by : Dr Samuel Inbaraja S
Download or read book A Short and Practical Textbook of Prompt Engineering written by Dr Samuel Inbaraja S and published by Samuel Inbaraja S. This book was released on 2023-12-06 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: Consider a scenario where you wish to engage in a conversation with a computer system that can not only understand your natural language but also respond in a meaningful and informative way. This is precisely the goal of prompt engineering, a technique that enables users to harness the power of large language models (LLMs) to perform a wide range of tasks, from generating creative text formats to answering questions, translating languages, and engaging in meaningful conversations. This practical textbook has examples in every chapter and practical exercises at various place to facilitate learning. There are 15 chapters with references and comprehensible content. Learn prompt engineering and improve your chances of landing a job in the new normal of the AI economy in the evolving AI civilization.
Book Synopsis Mastering Large Language Models with Python by : Raj Arun R
Download or read book Mastering Large Language Models with Python written by Raj Arun R and published by Orange Education Pvt Ltd. This book was released on 2024-04-12 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Book Synopsis The Prompt Engineer's Handbook by : Alex Stirling
Download or read book The Prompt Engineer's Handbook written by Alex Stirling and published by Mental Health Publishing. This book was released on 2024-01-10 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt: Are you ready to unleash the power of prompt engineering and embark on a thrilling 'midjourney' towards unlocking unlimited wealth? Look no further than The Prompt Engineer's Handbook: Unlocking Wealth through Words and Images! In this groundbreaking guide, acclaimed author and chatpgt expert, Alex Stirling, takes you on an exhilarating ride through the world of prompt engineering. Alex also reveals the secrets behind crafting compelling words and captivating images that will leave your audience spellbound, and providing a myriad of contexts where these words and images can be used to generate an income. Whether you're a seasoned entrepreneur looking to take your business to new heights or a student/mom/dad who is looking for a side hustle, this handbook is your ultimate tool. Discover innovative techniques for capturing attention, sparking curiosity, and driving action through carefully designed prompts, that ultimately generate money. Prepare yourself for a transformational experience as you uncover the hidden potential within you. Get ready to rewrite your story and unlock boundless wealth with The Prompt Engineer's Handbook. Your journey starts now!
Book Synopsis Data Intelligence and Cognitive Informatics by : I. Jeena Jacob
Download or read book Data Intelligence and Cognitive Informatics written by I. Jeena Jacob and published by Springer Nature. This book was released on 2024-02-07 with total page 579 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is a collection of peer-reviewed best selected research papers presented at the International Conference on Data Intelligence and Cognitive Informatics (ICDICI 2023), organized by SCAD College of Engineering and Technology, Tirunelveli, India, during June 27–28, 2023. This book discusses new cognitive informatics tools, algorithms and methods that mimic the mechanisms of the human brain which lead to an impending revolution in understating a large amount of data generated by various smart applications. The book includes novel work in data intelligence domain which combines with the increasing efforts of artificial intelligence, machine learning, deep learning and cognitive science to study and develop a deeper understanding of the information processing systems.
Book Synopsis Programming Large Language Models with Azure Open AI by : Francesco Esposito
Download or read book Programming Large Language Models with Azure Open AI written by Francesco Esposito and published by Microsoft Press. This book was released on 2024-04-22 with total page 604 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use LLMs to build better business software applications Autonomously communicate with users and optimize business tasks with applications built to make the interaction between humans and computers smooth and natural. Artificial Intelligence expert Francesco Esposito illustrates several scenarios for which a LLM is effective: crafting sophisticated business solutions, shortening the gap between humans and software-equipped machines, and building powerful reasoning engines. Insight into prompting and conversational programming—with specific techniques for patterns and frameworks—unlock how natural language can also lead to a new, advanced approach to coding. Concrete end-to-end demonstrations (featuring Python and ASP.NET Core) showcase versatile patterns of interaction between existing processes, APIs, data, and human input. Artificial Intelligence expert Francesco Esposito helps you: Understand the history of large language models and conversational programming Apply prompting as a new way of coding Learn core prompting techniques and fundamental use-cases Engineer advanced prompts, including connecting LLMs to data and function calling to build reasoning engines Use natural language in code to define workflows and orchestrate existing APIs Master external LLM frameworks Evaluate responsible AI security, privacy, and accuracy concerns Explore the AI regulatory landscape Build and implement a personal assistant Apply a retrieval augmented generation (RAG) pattern to formulate responses based on a knowledge base Construct a conversational user interface For IT Professionals and Consultants For software professionals, architects, lead developers, programmers, and Machine Learning enthusiasts For anyone else interested in natural language processing or real-world applications of human-like language in software
Book Synopsis Crafting Effective Prompts by : Subramanian Venkataraman
Download or read book Crafting Effective Prompts written by Subramanian Venkataraman and published by Independently Published. This book was released on 2024-03-02 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Prompt engineering is indeed an art, important for you effectively communicating with Large Language Models (LLMs) to get the results you want in a certain topic or context without any ambiguity Prompt engineering is a method where we give clear instructions or questions or we will input text, which are called prompts, to guide models like GPT-4 creating specific results and display them as output. AI models have undergone extensive training on vast datasets, leading to the release of numerous models catering to various industries. In this book, you will gain understanding on OpenAI, LLM, LLAMA2, LangChain, Transformer Model, Vector Store, HuggingFace and how to utilize them through the principles of Prompt Engineering using Prompt design techniques by solved programming examples written in Python. Upon completion of this reading, you will have gained hands on experience in Prompt engineering principles, empowering you to apply them effectively to develop new applications specific to your interest and requirements.
Book Synopsis HCI International 2023 Posters by : Constantine Stephanidis
Download or read book HCI International 2023 Posters written by Constantine Stephanidis and published by Springer Nature. This book was released on 2023-07-08 with total page 573 pages. Available in PDF, EPUB and Kindle. Book excerpt: The five-volume set CCIS 1832-1836 contains the extended abstracts of the posters presented during the 25th International Conference on Human-Computer Interaction, HCII 2023, which was held as a hybrid event in Copenhagen, Denmark, in July 2023. The total of 1578 papers and 396 posters included in the 47 HCII 2023 proceedings volumes were carefully reviewed and selected from the 7472 contributions.The posters presented in these five volumes are organized in topical sections as follows: Part I: HCI Design: Theoretical Approaches, Methods and Case Studies; Multimodality and Novel Interaction Techniques and Devices; Perception and Cognition in Interaction; Ethics, Transparency and Trust in HCI; User Experience and Technology Acceptance Studies.Part II: Supporting Health, Psychological Wellbeing, and Fitness; Design for All, Accessibility and Rehabilitation Technologies; Interactive Technologies for the Aging Population.Part III: Interacting with Data, Information and Knowledge; Learning and Training Technologies; Interacting with Cultural Heritage and Art.Part IV: Social Media: Design, User Experiences and Content Analysis; Advances in eGovernment Services; eCommerce, Mobile Commerce and Digital Marketing: Design and Customer Behavior; Designing and Developing Intelligent Green Environments; (Smart) Product Design.Part V: Driving Support and Experiences in Automated Vehicles; eXtended Reality: Design, Interaction Techniques, User Experience and Novel Applications; Applications of AI Technologies in HCI.
Book Synopsis Pretrain Vision and Large Language Models in Python by : Emily Webber
Download or read book Pretrain Vision and Large Language Models in Python written by Emily Webber and published by Packt Publishing Ltd. This book was released on 2023-05-31 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master the art of training vision and large language models with conceptual fundaments and industry-expert guidance. Learn about AWS services and design patterns, with relevant coding examples Key Features Learn to develop, train, tune, and apply foundation models with optimized end-to-end pipelines Explore large-scale distributed training for models and datasets with AWS and SageMaker examples Evaluate, deploy, and operationalize your custom models with bias detection and pipeline monitoring Book Description Foundation models have forever changed machine learning. From BERT to ChatGPT, CLIP to Stable Diffusion, when billions of parameters are combined with large datasets and hundreds to thousands of GPUs, the result is nothing short of record-breaking. The recommendations, advice, and code samples in this book will help you pretrain and fine-tune your own foundation models from scratch on AWS and Amazon SageMaker, while applying them to hundreds of use cases across your organization. With advice from seasoned AWS and machine learning expert Emily Webber, this book helps you learn everything you need to go from project ideation to dataset preparation, training, evaluation, and deployment for large language, vision, and multimodal models. With step-by-step explanations of essential concepts and practical examples, you'll go from mastering the concept of pretraining to preparing your dataset and model, configuring your environment, training, fine-tuning, evaluating, deploying, and optimizing your foundation models. You will learn how to apply the scaling laws to distributing your model and dataset over multiple GPUs, remove bias, achieve high throughput, and build deployment pipelines. By the end of this book, you'll be well equipped to embark on your own project to pretrain and fine-tune the foundation models of the future. What you will learn Find the right use cases and datasets for pretraining and fine-tuning Prepare for large-scale training with custom accelerators and GPUs Configure environments on AWS and SageMaker to maximize performance Select hyperparameters based on your model and constraints Distribute your model and dataset using many types of parallelism Avoid pitfalls with job restarts, intermittent health checks, and more Evaluate your model with quantitative and qualitative insights Deploy your models with runtime improvements and monitoring pipelines Who this book is for If you're a machine learning researcher or enthusiast who wants to start a foundation modelling project, this book is for you. Applied scientists, data scientists, machine learning engineers, solution architects, product managers, and students will all benefit from this book. Intermediate Python is a must, along with introductory concepts of cloud computing. A strong understanding of deep learning fundamentals is needed, while advanced topics will be explained. The content covers advanced machine learning and cloud techniques, explaining them in an actionable, easy-to-understand way.
Book Synopsis Mastering Large Language Models by : Sanket Subhash Khandare
Download or read book Mastering Large Language Models written by Sanket Subhash Khandare and published by BPB Publications. This book was released on 2024-03-12 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: Do not just talk AI, build it: Your guide to LLM application development KEY FEATURES ● Explore NLP basics and LLM fundamentals, including essentials, challenges, and model types. ● Learn data handling and pre-processing techniques for efficient data management. ● Understand neural networks overview, including NN basics, RNNs, CNNs, and transformers. ● Strategies and examples for harnessing LLMs. DESCRIPTION Transform your business landscape with the formidable prowess of large language models (LLMs). The book provides you with practical insights, guiding you through conceiving, designing, and implementing impactful LLM-driven applications. This book explores NLP fundamentals like applications, evolution, components and language models. It teaches data pre-processing, neural networks , and specific architectures like RNNs, CNNs, and transformers. It tackles training challenges, advanced techniques such as GANs, meta-learning, and introduces top LLM models like GPT-3 and BERT. It also covers prompt engineering. Finally, it showcases LLM applications and emphasizes responsible development and deployment. With this book as your compass, you will navigate the ever-evolving landscape of LLM technology, staying ahead of the curve with the latest advancements and industry best practices. WHAT YOU WILL LEARN ● Grasp fundamentals of natural language processing (NLP) applications. ● Explore advanced architectures like transformers and their applications. ● Master techniques for training large language models effectively. ● Implement advanced strategies, such as meta-learning and self-supervised learning. ● Learn practical steps to build custom language model applications. WHO THIS BOOK IS FOR This book is tailored for those aiming to master large language models, including seasoned researchers, data scientists, developers, and practitioners in natural language processing (NLP). TABLE OF CONTENTS 1. Fundamentals of Natural Language Processing 2. Introduction to Language Models 3. Data Collection and Pre-processing for Language Modeling 4. Neural Networks in Language Modeling 5. Neural Network Architectures for Language Modeling 6. Transformer-based Models for Language Modeling 7. Training Large Language Models 8. Advanced Techniques for Language Modeling 9. Top Large Language Models 10. Building First LLM App 11. Applications of LLMs 12. Ethical Considerations 13. Prompt Engineering 14. Future of LLMs and Its Impact
