Generative Ai Engineering
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| Author | : Ben Wilson |
| Publisher | : Simon and Schuster |
| Total Pages | : 879 |
| Release | : 2022-05-17 |
| Genre | : Computers |
| ISBN | : 1638356580 |
Field-tested tips, tricks, and design patterns for building machine learning projects that are deployable, maintainable, and secure from concept to production. In Machine Learning Engineering in Action, you will learn: Evaluating data science problems to find the most effective solution Scoping a machine learning project for usage expectations and budget Process techniques that minimize wasted effort and speed up production Assessing a project using standardized prototyping work and statistical validation Choosing the right technologies and tools for your project Making your codebase more understandable, maintainable, and testable Automating your troubleshooting and logging practices Ferrying a machine learning project from your data science team to your end users is no easy task. Machine Learning Engineering in Action will help you make it simple. Inside, you'll find fantastic advice from veteran industry expert Ben Wilson, Principal Resident Solutions Architect at Databricks. Ben introduces his personal toolbox of techniques for building deployable and maintainable production machine learning systems. You'll learn the importance of Agile methodologies for fast prototyping and conferring with stakeholders, while developing a new appreciation for the importance of planning. Adopting well-established software development standards will help you deliver better code management, and make it easier to test, scale, and even reuse your machine learning code. Every method is explained in a friendly, peer-to-peer style and illustrated with production-ready source code. About the technology Deliver maximum performance from your models and data. This collection of reproducible techniques will help you build stable data pipelines, efficient application workflows, and maintainable models every time. Based on decades of good software engineering practice, machine learning engineering ensures your ML systems are resilient, adaptable, and perform in production. About the book Machine Learning Engineering in Action teaches you core principles and practices for designing, building, and delivering successful machine learning projects. You'll discover software engineering techniques like conducting experiments on your prototypes and implementing modular design that result in resilient architectures and consistent cross-team communication. Based on the author's extensive experience, every method in this book has been used to solve real-world projects. What's inside Scoping a machine learning project for usage expectations and budget Choosing the right technologies for your design Making your codebase more understandable, maintainable, and testable Automating your troubleshooting and logging practices About the reader For data scientists who know machine learning and the basics of object-oriented programming. About the author Ben Wilson is Principal Resident Solutions Architect at Databricks, where he developed the Databricks Labs AutoML project, and is an MLflow committer.
| Author | : Anand Vemula |
| Publisher | : Independently Published |
| Total Pages | : 0 |
| Release | : 2024-07-03 |
| Genre | : Computers |
| ISBN | : |
Generative AI Engineering: Techniques, Tools, and Applications is a comprehensive guide that delves into the fascinating world of generative artificial intelligence (AI). This book is designed for AI practitioners, researchers, and enthusiasts who want to understand the principles, methodologies, and practical implementations of generative models. The journey begins with an introduction to generative AI, exploring its history, evolution, key applications, and the ethical considerations that come with this powerful technology. The fundamentals of machine learning and deep learning are covered next, laying a solid foundation with an overview of neural networks, their architectures, and common algorithms. The book then delves into the heart of generative AI with detailed chapters on various generative models. Variational Autoencoders (VAEs) are explored first, from their mathematical foundations to implementation and real-world applications. This is followed by a deep dive into Generative Adversarial Networks (GANs), examining their architecture, training techniques, and different variants like DCGAN and StyleGAN. Autoregressive models, including RNNs, LSTMs, and Transformers, are discussed next, highlighting their training and optimization techniques. Diffusion models, with their unique approach to generating data through noise reduction, are also thoroughly explained. Advanced topics in generative AI are explored, including transfer learning, few-shot and zero-shot learning, and the integration of reinforcement learning. Hybrid models that combine different generative approaches are also discussed. Practical implementation guides provide step-by-step instructions for building, training, and deploying generative models using popular tools and libraries like TensorFlow, PyTorch, and Keras. Evaluation and metrics chapters offer insights into assessing the performance of generative models using qualitative and quantitative measures. The book also covers diverse applications and case studies, showcasing the impact of generative AI in fields such as image and text generation, music and audio synthesis, video creation, healthcare, and the creative industries. Finally, the book addresses current challenges in generative AI, including ethical and societal impacts, and outlines future research directions that promise to drive the field forward.
| Author | : Ian Khan |
| Publisher | : John Wiley & Sons |
| Total Pages | : 485 |
| Release | : 2024-03-19 |
| Genre | : Business & Economics |
| ISBN | : 1394243332 |
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.
| Author | : James Phoenix |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 423 |
| Release | : 2024-05-16 |
| Genre | : Computers |
| ISBN | : 1098153405 |
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
| Author | : Anh Nguyen-Duc |
| Publisher | : Springer Nature |
| Total Pages | : 346 |
| Release | : |
| Genre | : |
| ISBN | : 3031556429 |
| Author | : Lance Eliot |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2024-03-19 |
| Genre | : Business & Economics |
| ISBN | : 9781957386164 |
| Author | : ARMANDO. BANACHEWICZ FANDANGO (KONRAD.) |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2023 |
| Genre | : |
| ISBN | : 9781805120513 |
| Author | : Prabhu TL |
| Publisher | : NestFame Creations Pvt Ltd. |
| Total Pages | : 224 |
| Release | : |
| Genre | : Computers |
| ISBN | : |
In the era of groundbreaking technological advancements, the book "100 Best Generative AI Tools" is your passport to an exhilarating expedition through the realms of creativity, imagination, and innovation. This captivating guide unveils a curated selection of the most remarkable and transformative generative AI tools that are reshaping the landscape of human ingenuity across a multitude of industries. Unlocking the Power of Generative AI: Imagine a world where machines possess the remarkable ability to generate art, music, literature, and even entire virtual realities. In "100 Best Generative AI Tools," you'll venture into this awe-inspiring realm, where algorithms fuse with creativity to produce captivating and unprecedented results. Whether you're an artist, a musician, a writer, or an innovator, this book empowers you to harness the potential of generative AI to amplify your creative endeavors. A Treasury of Creative Possibilities: This book serves as a treasure trove of innovative generative AI tools, meticulously curated to offer a diverse and comprehensive range of applications. From producing mesmerizing visual masterpieces to composing evocative musical compositions, and from crafting compelling narratives to designing immersive virtual landscapes—each tool is a gateway to limitless creative possibilities. Behind the Algorithmic Curtain: Delve deeper into the intricate workings of these generative AI tools as you unravel the science behind the algorithms. "100 Best Generative AI Tools" deciphers complex concepts into accessible insights, making it a captivating read for both enthusiasts and those new to the field. Explore how neural networks, deep learning, and cutting-edge technology collaborate harmoniously to produce works of art that rival human creativity. Crossing Boundaries and Industries: The impact of generative AI knows no bounds, transcending industries and reshaping the way we perceive creativity. Whether you're a fashion designer pushing the boundaries of design, a game developer crafting immersive digital experiences, or a scientist generating data-driven insights, the tools showcased in this book will spark your imagination and transform your approach to innovation. Empowering Creative Minds: "100 Best Generative AI Tools" goes beyond mere description; it provides you with the tools and knowledge to unleash your creative potential. Whether you're a curious novice or an experienced artist, this book equips you with the resources to embark on a journey of experimentation, discovery, and artistic evolution. Shape the Future of Creativity: As you delve into the pages of "100 Best Generative AI Tools," you become part of a transformative movement that is redefining the boundaries of human creativity. With these tools at your fingertips, you have the power to amplify your artistic voice, challenge traditional norms, and craft a future where the fusion of AI and imagination knows no limits. Join the Creative Revolution: Are you ready to join the ranks of visionaries who are seamlessly blending art, technology, and innovation? "100 Best Generative AI Tools" is your guide to embracing the future, where the canvas of creativity knows no boundaries and the brush strokes of imagination are powered by algorithms. Step into a world where your creative potential knows no limits, and let the journey of innovation begin.
| Author | : Anand Vemula |
| Publisher | : Anand Vemula |
| Total Pages | : 54 |
| Release | : |
| Genre | : Computers |
| ISBN | : |
A comprehensive guide to mastering the art and science of crafting effective prompts to unleash the full potential of generative AI. This book delves into the principles, techniques, and ethical considerations of prompt engineering, providing readers with practical insights and strategies for achieving optimal results. The book begins by exploring the fundamentals of prompt engineering, including the definition of prompts, their importance in guiding AI models, and the various types of prompts commonly used. Readers will learn about the common challenges and pitfalls of prompt engineering and gain a deeper understanding of AI models, their architecture, training processes, strengths, and limitations. Moving on to advanced topics, the book covers multi-turn prompts, contextual and sequential prompts, and leveraging model outputs to refine and enhance AI-generated content. Readers will discover domain-specific applications of prompt engineering, including creative writing, conversational AI, visual and artistic applications, and scientific and technical domains. Ethical considerations play a significant role in prompt engineering, and the book provides insights into recognizing and mitigating bias, ethical considerations, and responsible AI use. Readers will also gain practical knowledge of the tools and platforms available for prompt engineering, along with techniques for customizing and extending AI models. Testing and evaluation are essential aspects of prompt engineering, and the book offers guidance on metrics for assessing prompt performance, gathering user feedback, and conducting A/B testing and comparative analysis. Real-world case studies highlight successful applications of prompt engineering across various industries, offering valuable lessons and insights. Finally, the book explores future trends in generative AI and prompt engineering, providing readers with a glimpse into emerging technologies, predictions for the future of AI, and strategies for preparing for future developments. With its comprehensive coverage and practical insights, "Prompt Engineering for Generative AI" is an indispensable resource for AI enthusiasts, researchers, developers, and anyone looking to harness the power of generative AI through effective prompt engineering
| Author | : QuickRead |
| Publisher | : QuickRead.com |
| Total Pages | : 21 |
| Release | : |
| Genre | : Study Aids |
| ISBN | : |
Learn how China was able to catch up to the US as an AI superpower and discover the future of artificial intelligence. As we live in a world where cars no longer need drivers, phones can be unlocked with facial recognition, and the internet can even provide advertisements based on your browsing history, it’s becoming more and more apparent that artificial intelligence (AI) is only going to get better. While the AI movement began in the United States, other countries have quickly caught up, including China who is now one of the largest AI superpowers in the world. However, the two countries continue to compete in the AI race and the two take drastically different approaches. For instance, China is determined to become the world leader and is doing whatever it takes to get there, including funneling billions of dollars into AI tech start-ups and making it as easy as possible to launch a new start-up. As Silicon Valley competes with its Chinese counterpart, Zhongguancun, Kai-Fu Lee discusses everything, including what led to China’s success, what the future of AI looks like, and how a change in values can make our world a better place. Do you want more free books like this? Download our app for free at https://www.QuickRead.com/App and get access to hundreds of free book and audiobook summaries. DISCLAIMER: This book summary is meant as a preview and not a replacement for the original work. If you like this summary please consider purchasing the original book to get the full experience as the original author intended it to be. If you are the original author of any book on QuickRead and want us to remove it, please contact us at [email protected].
