Название: Prompt Engineering for LLMs: The Art and Science of Building Large Language Model-Based Applications
Автор: John Berryman, Albert Ziegler
Издательство: O’Reilly Media, Inc.
Год: 2025
Страниц: 282
Язык: английский
Формат: True/Retail PDF, True/Retail EPUB
Размер: 22.5 MB

Large language models (LLMs) are revolutionizing the world, promising to automate tasks and solve complex problems. A new generation of software applications are using these models as building blocks to unlock new potential in almost every domain, but reliably accessing these capabilities requires new skills. This book will teach you the art and science of prompt engineering-the key to unlocking the true potential of LLMs. Industry experts John Berryman and Albert Ziegler share how to communicate effectively with AI, transforming your ideas into a language model-friendly format. By learning both the philosophical foundation and practical techniques, you'll be equipped with the knowledge and confidence to build the next generation of LLM-powered applications. Understand LLM architecture and learn how to best interact with it Design a complete prompt-crafting strategy for an application Gather, triage, and present context elements to make an efficient prompt Master specific prompt-crafting techniques like few-shot learning, chain-of-thought prompting, and RAG.

Название: Mastering Number Theory in Python: Unlocking the Secrets of Prime Numbers and the Riemann Hypothesis
Автор: Jamie Flux
Издательство: Independently published
Год: 2024
Страниц: 206
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB

This comprehensive book delves into the intricate world of advanced Number Theory. The book covers foundational concepts, classic algorithms and theorems, advanced topics, analytic Number Theory, additive and multiplicative Number Theory, special Number Theoretic functions, cryptographic applications, computationally intensive problems, advanced mathematical tools, probabilistic Number Theory, and computational Number Theory. With each chapter, readers will gain a deeper understanding of the complexities and beauty of Number Theory and its wide-ranging applications in various fields including cryptography, Computer Science, and physics. This book is a valuable resource for mathematicians, researchers, and students interested in the fascinating world of Number Theory and its many intricate aspects.

Название: Mastering Shell for DevOps: Automate, streamline, and secure DevOps workflows with modern shell scripting
Автор: Gilbert Stew
Издательство: GitforGits
Год: 2024
Страниц: 255
Язык: английский
Формат: pdf, azw3, epub, mobi
Размер: 10.1 MB

"Mastering Shell for DevOps" is all about giving DevOps, cloud, and Linux folks the know-how to automate and make their workflows more efficient with shell scripting. The book uses real-world examples and simple instructions to show how to automate tasks and move away from manual work in a DevOps environment. We start with the basics of shell scripting, so you can learn to write scripts that get the job done. It then moves on to version control with Git and GitHub, showing the importance of collaboration and code management in this context. The book then jumps into infrastructure provisioning and configuration management, showing you how to automate the setup of servers and services using tools like AWS CLI, Docker, and Kubernetes. As your skills grow, you'll learn to set up monitoring and logging tools, automate incident detection and resolution, and manage network traffic and load balancing. The book also helps you learn how to automate security tasks, including user access management, vulnerability scanning, patching, and compliance checks. By the end of the book, you'll have a whole toolkit of shell scripts that will help you work more efficiently, reliably, and securely in your DevOps practices.

Название: Machine Learning Mathematics in Python
Автор: Jamie Flux
Издательство: Independently published
Год: 2024
Страниц: 238
Язык: английский
Формат: pdf
Размер: 10.1 MB

This book delves into the intricate relationship between mathematics and Machine Learning, providing readers with a comprehensive understanding of the mathematical concepts that underpin modern AI. From linear algebra and calculus to probability theory and statistics, each chapter explores a different mathematical topic and its application in machine learning. Throughout the book, readers will learn about fundamental concepts such as regression, classification, clustering, and Deep Learning, as well as advanced topics like reinforcement learning, GANs, and quantum machine learning. With a focus on both theoretical foundations and practical applications, "Machine Learning Mathematics" is an indispensable resource for anyone looking to deepen their understanding of the mathematical principles that drive contemporary AI algorithms. This book aims to bridge the gap between mathematics and Machine Learning, showcasing the critical role of mathematics in solving complex data-driven tasks. Each chapter presents key mathematical concepts, accompanied by clear explanations and Python code samples, ensuring that readers can grasp the underlying principles.

Название: Functional Design and Architecture: Examples in Haskell (Final)
Автор: Alexander Granin
Издательство: Manning Publications
Год: 2025
Страниц: 456
Язык: английский
Формат: epub (true)
Размер: 10.1 MB

Design patterns and architectures for building production quality applications using functional programming. Functional Design and Architecture is a pioneering guide to software engineering using Haskell and other functional languages. In it, you’ll discover Functional Declarative Design and other design principles perfect for working in Haskell, PureScript, F#, and Scala. Functional Design and Architecture lays out a comprehensive and complete approach to software design that utilizes the powerful and fascinating ideas of functional programming. Its examples are in Haskell, but its universal principles can be put into practice with any functional programming language. Inside, you’ll find cutting-edge functional design principles and practices for every stage of application development, from architecting your application through to running simple and maintainable tests. For experienced developers who know a functional language.

Название: Ren'Py. Создаем игры и приложения
Автор: Адонин А. С.
Издательство: Наука и техника
Год: 2024
Формат: PDF
Страниц: 402
Размер: 68 Mb
Язык: Русский

Игровой движок Ren'Py (РенПи) - это один из простейших способов познакомиться с основами программирования. Благодаря этой книге, шаг за шагом создавая свою первую игру, вы познакомитесь с основами разработки игр. Функционал движка настолько прост, что первую свою игру вы сможете запустить уже спустя несколько первых глав.

Название: Data Engineering Design Patterns: Recipes for Solving the Most Common Data Engineering Problems (3rd Early Release)
Автор: Bartosz Konieczny
Издательство: O’Reilly Media, Inc.
Год: 2024-10-16
Страниц: 340
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB

Data projects are an intrinsic part of an organization's technical ecosystem, but data engineers in many companies are still trying to solve problems that others have already solved. This hands-on guide shows you how to provide valuable data by focusing on various aspects of data engineering, including data ingestion, data quality, idempotency, and more. Author Bartosz Konieczny guides you through the process of building reliable end-to-end data engineering projects, from data ingestion to data observability, focusing on data engineering design patterns that solve common business problems in a secure and storage-optimized manner. Each pattern includes a user-facing description of the problem, solutions, and consequences that place the pattern into the context of real-life scenarios.

Название: Python Coding for Beginners - 20th Edition 2024
Автор: Papercut Limited
Издательство: Papercut Limited
Год: 2024
Язык: английский
Формат: pdf
Размер: 44.9 MB

"Программирование на Python для начинающих" - это первый и единственный выбор, если вы начинающий и хотите узнать все, что вам нужно, чтобы начать программировать. Это независимое руководство наполнено полезными рекомендациями и пошаговыми примерами с цветными иллюстрациями, написанными на простом и понятном английском языке. На страницах этого нового руководства вы узнаете все, что вам нужно знать о написании своих собственных потрясающих приложений. С этим неофициальным руководством по эксплуатации ни одна проблема не будет неразрешимой, ни один вопрос не останется без ответа, пока вы учитесь, изучаете и улучшаете свой пользовательский опыт.

Название: Hands-On Generative AI with Transformers and Diffusion Models (6th Early Release)
Автор: Omar Sanseviero, Pedro Cuenca, Apolinario Passos, Jonathan Whitaker
Издательство: O’Reilly Media, Inc.
Год: 2024-09-06
Страниц: 419
Язык: английский
Формат: epub
Размер: 28.7 MB

Learn how to use generative media techniques with AI to create novel images or music in this practical, hands-on guide. Data scientists and software engineers will understand how state-of-the-art generative models work, how to fine-tune and adapt them to your needs, and how to combine existing building blocks to create new models and creative applications in different domains. This book introduces theoretical concepts in an intuitive way, with extensive code samples and illustrations that you can run on services such as Google Colaboratory, Kaggle, or Hugging Face Spaces with minimal setup. You'll learn how to use open source libraries such as Transformers and Diffusers, conduct code exploration, and study several existing projects to help guide your work. This book assumes that you are comfortable programming in Python and have a foundational understanding of what Machine Learning is, including basic usage of frameworks like PyTorch or TensorFlow.

Название: Machine Learning and Metaheuristic Computation
Автор: Erik Cuevas, Jorge Galvez, Omar Avalos, Fernando Wario
Издательство: Wiley-IEEE Press
Год: 2025
Страниц: 418
Язык: английский
Формат: pdf, epub (true)
Размер: 30.3 MB

Learn to bridge the gap between Machine Learning and metaheuristic methods to solve problems in optimization approaches. Few areas of technology have greater potential to revolutionize the globe than Artificial Intelligence. Two key areas of Artificial Intelligence, Machine Learning and metaheuristic computation, have an enormous range of individual and combined applications in Computer Science and technology. To date, these two complementary paradigms have not always been treated together, despite the potential of a combined approach which maximizes the utility and minimizes the drawbacks of both. Machine Learning and Metaheuristic Computation offers an introduction to both of these approaches and their joint applications. Both a reference text and a course, it is built around the popular Python programming language to maximize utility. It guides the reader gradually from an initial understanding of these crucial methods to an advanced understanding of cutting-edge Artificial Intelligence tools. For enthusiasts and practitioners in Machine Learning who may not be well-versed in metaheuristic computation, this book is an essential resource.