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 Название: Prompt Engineering for Generative AI: Future-Proof Inputs for Reliable AI Outputs at Scale (Final Release)
Автор: James Phoenix, Mike Taylor
Издательство: O’Reilly Media, Inc.
Год: 2024
Страниц: 423
Язык: английский
Формат: True PDF, True EPUB (Retail Copy)
Размер: 39.8 MB, 33.3 MB
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. All of the code in this book is in Python and was designed to be run in a Jupyter Notebook or Google Colab notebook. The concepts taught in the book are transferable to javascript or any other coding language if preferred, though the primary focus of this book is on prompting techniques rather than traditional coding skills. The code can all be found on GitHub, and we will link to the relevant notebooks throughout. It’s highly recommended that you utilize the GitHub repository and run the provided examples while reading the book. | |
Разместил: Ingvar16 6-06-2024, 19:19 | Комментарии: 0 | Подробнее
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Название: Python на примерах. Практика, практика и только практика
Автор: Кольцов Д.М.
Издательство: НиТ
Год: 2023
Формат: pdf
Размер: 13 Мб
Качество: Хорошее
Язык: Русский
Данная книга является сборником различных задач и примеров, решенных с помощью языка программирования Python. Также в книге рассмотрена базовая теоретическая часть Python, позволяющая ориентироваться в языке и создавать свои программы. Теория сопровождается большим количеством разнообразных примеров - от самых основ (переменные и типы данных; операторы и циклы; математические функции и регулярные выражения; строки, списки, кортежи и т.д.) - до более продвинутых тем (объектно-ориентированное программирование; модули и пакеты в Python, генераторы и итераторы; метапрограммирование и т.д.).
Книга будет полезна как для тех, кто только заинтересовался Python, так и для тех, кто хочет улучшить свои навыки в программировании на Python. | |
Разместил: tanyavip1 6-06-2024, 18:36 | Комментарии: 0 | Подробнее
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Название: 40 задач на Python
Автор: Джеймс Девис
Издательство: Автор
Год: 2024
Формат: PDF
Страниц: 90
Размер: 1 Mb
Язык: Русский
Книга призвана помочь читателю развить свои математические навыки, улучшить логическое мышление, освоить использование языка программирования Python для решения задач. Она подходит как для самостоятельного изучения, так и в качестве учебного пособия для студентов и учителей, желающих более глубоко погрузиться в мир языка Python и его приложений с использованием современных инструментов. В книге представлены задачи из разных областей: геометрические, комбинаторные, задачи на вероятности и статистику, логические, арифметические, задачи на движение и скорость и задачи на рекурсию и последовательности.
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Разместил: Chipa 6-06-2024, 17:57 | Комментарии: 0 | Подробнее
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 Название: Machine Learning for Finance: Master Financial Strategies with Python-Powered Machine Learning
Автор: Hayden Van Der Post, Vincent Bisette
Издательство: Reactive Publishing
Год: 2024
Страниц: 553
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.1 MB
Unlock the full potential of your financial analysis with "Machine Learning for Finance." This comprehensive guide takes you from the basics of Python programming to advanced Machine Learning techniques tailored specifically for financial applications. Perfect for finance professionals, data scientists, and anyone eager to harness the power of AI in finance. Written by an industry expert, "Machine Learning for Finance" bridges the gap between finance and technology, equipping you with the tools to make data-driven decisions and stay ahead in the competitive financial landscape. Whether you're a seasoned professional or a curious beginner, this book is your ultimate resource for mastering the intersection of finance and Machine Learning. Machine Learning is an intricate and powerful tool that holds immense potential for transforming the financial industry. By leveraging sophisticated algorithms and vast datasets, it enables more accurate predictions, better risk management, and innovative financial solutions. As we continue to explore its applications, the boundary between human insight and artificial intelligence in finance increasingly blurs, heralding a new era of financial intelligence. Transform your financial strategies with Python and join the future of finance today! | |
Разместил: Ingvar16 6-06-2024, 15:45 | Комментарии: 0 | Подробнее
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 Название: Python Machine Learning for Beginners: Unlocking the Power of Data. A Beginner's Guide to Machine Learning with Python
Автор: Daniel Garfield
Издательство: May Reads
Год: 2024
Страниц: 148
Язык: английский
Формат: pdf, azw3, epub, mobi
Размер: 10.1 MB
"Python Machine Learning for Beginners: Unlocking the Power of Data" is a comprehensive beginner's guide that demystifies the world of Machine Learning using the Python programming language. Whether you are a student, a professional looking to expand your skillset, or simply curious about the fascinating field of Machine Learning, this book is your gateway to unlocking the power of data. In this book, you will embark on a journey that takes you from the fundamentals of Python programming to understanding the core principles and techniques of Machine Learning. Step by step, you will learn how to preprocess and explore data, engineer features, build predictive models, and evaluate their performance. With hands-on examples and practical exercises, you will gain a solid foundation in supervised and unsupervised learning algorithms, including linear regression, logistic regression, decision trees, random forests, support vector machines, clustering, and dimensionality reduction. Throughout the book, the emphasis is on making complex concepts accessible to beginners. With clear explanations, code snippets, and illustrative visualizations, you will develop a deep understanding of Machine learning techniques and their practical implementation using Python's popular libraries such as Scikit-learn, TensorFlow, and Keras. | |
Разместил: Ingvar16 6-06-2024, 15:11 | Комментарии: 0 | Подробнее
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 Название: From Ruby to Elixir: Unleash the Full Potential of Functional Programming
Автор: Stephen Bussey
Издательство: Pragmatic Bookshelf
Год: June 2024 (P1.0)
Страниц: 213
Язык: английский
Формат: pdf (true), epub
Размер: 10.1 MB
Elixir will change the way you think about programming. Use your Ruby experience to quickly get up to speed so you can see what all of the buzz is about. Go from zero to production applications that are reliable, fast, and scalable. Learn Elixir syntax and pattern matching to conquer the basics. Then move onto Elixir's unique process model that offers a world-class way to go parallel without fear. Finally, use the most common libraries like Ecto, Phoenix, and Oban to build a real-world SMS application. Now's the time. Dive in and learn Elixir. Whether you're a seasoned Ruby developer looking to expand your skill set or a programming beginner looking for a solid foundation in Elixir, this book has what you need to get up to speed quickly. Elixir is a functional language with a fairly small footprint. This makes it easier to learn and put into production than other languages. Plus, it's built on forty-year-old foundations that give your applications rock-solid stability. This book is organized into two parts. Part I is focused entirely on the fundamentals of the Elixir language. You’ll learn how to read and write Elixir code during this part of the book, which will be necessary in Part II. We’ll also cover slightly more advanced topics such as GenServer and the full power of pattern matching. Each section of Part I is designed to be completely stand-alone. The code examples are all chapter-specific, so you won’t be in the dark if you decide to start out of order. Part II is where theory meets practice. You’ll write a real application that uses an API to send and receive text messages. | |
Разместил: Ingvar16 6-06-2024, 13:59 | Комментарии: 0 | Подробнее
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Название: Микросервисы. Паттерны разработки и рефакторинга (2023)
Автор: Ричардсон К
Издательство: СПб.: Питер
Год: 2023
Формат: pdf
Страниц: 544
Размер: 25 mb
Язык: Русский
Если вам давно кажется, что вся разработка и развертывание в вашей компании донельзя замедлились - переходите на микросервисную архитектуру. Она обеспечивает непрерывную разработку, доставку и развертывание приложений любой сложности.
Книга, предназначенная для разработчиков и архитекторов из больших корпораций, рассказывает, как проектировать и писать приложения в духе микросервисной архитектуры. Также в ней описано, как делается рефакторинг крупного приложения - и монолит превращается в набор микросервисов. | |
Разместил: na5ballov 6-06-2024, 13:43 | Комментарии: 0 | Подробнее
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 Название: Artificial Intelligence and Internet of Things based Augmented Trends for Data Driven Systems
Автор: Anshu Singla, Sarvesh Tanwar, Pao?Ann Hsiung
Издательство: CRC Press
Серия: Intelligent Data?Driven Systems and Artificial Intelligence
Год: 2024
Страниц: 297
Язык: английский
Формат: pdf (true)
Размер: 11.1 MB
This book comprehensively discusses the role of cloud computing in Artificial Intelligence-based data-driven systems, and hybrid cloud computing for large data-driven applications. It further explores new approaches, paradigms, and frameworks to meet societal challenges by providing solutions for critical insights into data. The text provides internet of things-based frameworks and advanced computing techniques to deal with online/virtual systems. The resource?constrained nature of IoT devices leads to not only the challenges of privacy and autonomy but also the major challenge of implementing Machine Learning models for IoT devices. The implementation of Machine Learning models on IoT devices in real?time scenarios poses a major challenge that attracts researchers to work in this domain. To make the IoT ecosystems intelligent, these resource?constrained devices need to be analysed locally. As of now, all sensed data are being processed and analysed in clouds. The small IoT devices may not afford Machine Learning algorithms because of their limited computational power and memory requirements. This involves issues like low bandwidth, high latency, privacy, security and others. Also, there are several Machine Learning algorithms that can be applied for IoT data analytics especially for data?driven systems. Therefore, choosing the best model which is application specific is great work of thought. | |
Разместил: Ingvar16 6-06-2024, 13:02 | Комментарии: 0 | Подробнее
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 Название: Intermediate C Programming, 2nd Edition
Автор: Yung-Hsiang Lu, George K. Thiruvathukal
Издательство: CRC Press
Год: 2024
Страниц: 1079
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB
Revised for a new second edition, Intermediate C Programming provides a stepping-stone for intermediate-level students to go from writing short programs to writing real programs well. It shows students how to identify and eliminate bugs, write clean code, share code with others, and use standard Linux-based tools, such as ddd and valgrind. This second edition provides expanded coverage of these topics with new material focused on software engineering, including version control and unit testing. The text enhances their programming skills by explaining programming concepts and comparing common mistakes with correct programs. It also discusses how to use debuggers and the strategies for debugging as well as studies the connection between programming and discrete mathematics. Very few books are written for intermediate-level readers. They know something about programming already and are not surprised when they see if or while. They know how to create functions and call functions. They can write short programs, perhaps dozens of lines of code. However, they are not ready to handle thousand-line programs. They make mistakes sometimes. Most books talk about how to write correct programs without much help with avoiding common mistakes. The readers are unfamiliar with many concepts and tools that can help them write better programs. These readers need a stepping stone to take them from being capable of writing short programs to writing real programs. | |
Разместил: Ingvar16 6-06-2024, 12:32 | Комментарии: 0 | Подробнее
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 Название: Attacks, Defenses and Testing for Deep Learning
Автор: Jinyin Chen, Ximin Zhang, Haibin Zheng
Издательство: Springer
Год: 2024
Страниц: 413
Язык: английский
Формат: pdf (true)
Размер: 16.1 MB
This book provides a systematic study on the security of Deep Learning. With its powerful learning ability, Deep Learning is widely used in CV, FL, GNN, RL, and other scenarios. However, during the process of application, researchers have revealed that Deep Learning is vulnerable to malicious attacks, which will lead to unpredictable consequences. Take autonomous driving as an example, there were more than 12 serious autonomous driving accidents in the world in 2018, including Uber, Tesla and other high technological enterprises. Drawing on the reviewed literature, we need to discover vulnerabilities in Deep Learning through attacks, reinforce its defense, and test model performance to ensure its robustness. The book aims to provide a comprehensive introduction to the methods of attacks, defenses, and testing evaluations for deep learning in various scenarios. We focus on multiple application scenarios such as computer vision, Federated Learning, graph neural networks, and Reinforcement Learning, considering multiple security issues that exist under different data modalities, model structures, and tasks. Testing deep neural networks is an effective method to measure the security and robustness of Deep Learning models. Through test evaluation, security vulnerabilities and weaknesses in deep neural networks can be identified. By identifying and fixing these vulnerabilities, the security and robustness of the model can be improved. The book is divided into three main parts: attacks, defenses, and testing. In the attack section, we introduce in detail the attack methods and techniques targeting Deep Learning models. | |
Разместил: Ingvar16 5-06-2024, 16:31 | Комментарии: 0 | Подробнее
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