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 Название: Microsoft Semantic Kernel in Action (MEAP v3)
Автор: Daniel Costea
Издательство: Manning Publications
Год: 2025
Страниц: 308
Язык: английский
Формат: pdf, epub
Размер: 13.2 MB
Build AI applications that integrate multiple models, data sources, and other components using Microsoft Semantic Kernel. Even simple AI applications need to combine LLMs and other models, functions and plugins created in various programming languages, and custom data sources. With the Microsoft Semantic Kernel SDK, you can create chatbots, copilots, and agents by chaining individual components together using a few lines of glue code. Semantic Kernel makes it a snap to build AI apps from scratch or integrate AI features into an existing codebase. Microsoft Semantic Kernel in Action teaches you to create AI applications and integrate AI into existing software using C# and the lightweight Semantic Kernel SDK. The book covers both proprietary AI models like OpenAI's GPT and open-source options like Llama and Phi. For beginner and expert .NET developers, data scientists, and AI enthusiasts seeking to integrate AI into applications. | |
Разместил: Ingvar16 12-06-2025, 18:16 | Комментарии: 0 | Подробнее
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 Название: R for Non-Programmers
Автор: Daniel Dauber
Издательство: CRC Press
Год: 2025
Страниц: 384
Язык: английский
Формат: epub (true)
Размер: 10.1 MB
Unlock the Power of Data Analysis with R. Whether you are a researcher, student, or professional new to programming, this book provides a step-by-step guide to mastering R for quantitative and mixed-methods analysis. Designed for those who still need to gain program- ming experience or wish to learn a new one, it demystifies data analysis, helping you tackle challenges from data wrangling to statistical modelling. Packed with practical examples, engaging explanations, and real-world applications, this book equips you with the tools to analyse data confidently, identify trends, and uncover meaningful insights. This book, which strongly focuses on reproducible research, is an indispensable guide for anyone looking to enhance their analytical toolkit and unlock R’s full potential for data analysis and statistical modelling. | |
Разместил: Ingvar16 12-06-2025, 16:30 | Комментарии: 0 | Подробнее
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 Название: Осваиваем архитектуру Transformer: Разработка современных моделей с помощью передовых методов обработки естественного языка
Автор: Йылдырым C., Асгари-Ченаглу М.
Издательство: ДМК Пресс
Год: 2022
Cтраниц: 320
Формат: pdf
Размер: 18 мб
Язык: русский
В этой книге рассказывается, как создавать различные приложения NLP на основе трансформеров, используя библиотеку Python Transformers. Вы познакомитесь с архитектурой трансформеров и напишете свою первую программу для работы с моделями на основе этой передовой технологии. Вашему вниманию будут представлены эффективные модели c открытым исходным кодом для решения сложных задач и тестовые наборы данных; вы освоите методы многоязычной и межъязыковой обработки текстов, научитесь оптимизировать модели и узнаете, как добиться для этих моделей интерпретируемости и объяснимости. | |
Разместил: rivasss 12-06-2025, 13:07 | Комментарии: 0 | Подробнее
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 Название: Investing for Programmers (MEAP v5)
Автор: Stefan Papp
Издательство: Manning Publications
Год: 2025
Страниц: 340
Язык: английский
Формат: pdf, epub
Размер: 21.8 MB
Maximize your portfolio, analyze markets, and make data-driven investment decisions using Python and Generative AI. Programmers have a unique superpower when it comes to managing financial stock analysis, price forecasting, and strategic investing. Using popular open-source Python libraries and cutting-edge AI tools, you can do the kind of sophisticated analysis that’s normally limited to expensive software and financial professionals. This book shows you how! In Investing for Programmers, you’ll work with a familiar stack of Python tools—including Pandas, NumPy, and Matplotlib—to dissect stock market data, uncover patterns, and build predictive models. Real-life examples help you build your own intuition about financial markets. For Python programmers with data analysis experience. Only the most basic investing knowledge is needed. If you've traded stocks in an online platform or made retirement plan decisions, you're ready to begin. | |
Разместил: Ingvar16 12-06-2025, 04:44 | Комментарии: 0 | Подробнее
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 Название: Domain-Specific Small Language Models (MEAP v3)
Автор: Guglielmo Iozzia
Издательство: Manning Publications
Год: 2025
Страниц: 237
Язык: английский
Формат: pdf, epub
Размер: 13.5 MB
Bigger isn’t always better. Train and tune highly focused language models optimized for domain specific tasks. When you need a language model to respond accurately and quickly about a specific field of knowledge, the sprawling capacity of a LLM may hurt more than it helps. Domain-Specific Small Language Models teaches you to build generative AI models optimized for specific fields. Domain-Specific Small Language Models teaches you how to create language models that deliver the power of LLMs for specific areas of knowledge. You’ll learn to minimize the computational horsepower your models require, while keeping high–quality performance times and output. You’ll appreciate the clear explanations of complex technical concepts alongside working code samples you can run and replicate on your laptop. Plus, you’ll learn to develop and deliver RAG systems and AI agents that rely solely on SLMs, and without the costs of foundation model access. For Machine Learning engineers familiar with Python. | |
Разместил: Ingvar16 12-06-2025, 03:09 | Комментарии: 0 | Подробнее
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 Название: Data Pipelines with Apache Airflow, Second Edition (MEAP v12)
Автор: Julian de Ruiter, Ismael Cabral, Kris Geusebroek, Daniel van der Ende, Bas Harenslak
Издательство: Manning Publications
Год: 2025
Страниц: 645
Язык: английский
Формат: pdf, epub
Размер: 47.9 MB
Simplify, streamline, and scale your data operations with data pipelines built on Apache Airflow. Apache Airflow provides a batteries-included platform for designing, implementing, and monitoring data pipelines. Building pipelines on Airflow eliminates the need for patchwork stacks and homegrown processes, adding security and consistency to the process. Now in its second edition, Data Pipelines with Apache Airflow teaches you to harness this powerful platform to simplify and automate your data pipelines, reduce operational overhead, and seamlessly integrate all the technologies in your stack. This book focuses on Apache Airflow, a batch-oriented framework for building data pipelines. Airflow’s key feature is that it enables you to easily build scheduled data pipelines using Python, while also providing many building blocks that allow you to stitch together the many different technologies encountered in modern technological landscapes. For DevOps, data engineers, Machine Learning engineers, and sysadmins with intermediate Python skills. | |
Разместил: Ingvar16 12-06-2025, 02:11 | Комментарии: 0 | Подробнее
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 Название: Integrating Neurocomputing with Artificial Intelligence
Автор: Abhishek Kumar, Pramod Singh Rathore, Sachin Ahuja, Umesh Kumar Lilhore
Издательство: Wiley-Scrivener
Год: 2025
Страниц: 327
Язык: английский
Формат: pdf (true)
Размер: 33.6 MB
Integrating Neurocomputing with Artificial Intelligence provides unparalleled insights into the cutting-edge convergence of neuroscience and computing, enriched with real-world case studies and expert analyses that harness the transformative potential of neurocomputing in various disciplines. Integrating Neurocomputing with Artificial Intelligence is a comprehensive volume that delves into the forefront of the neurocomputing landscape, offering a rich tapestry of insights and cutting-edge innovations. This volume unfolds as a carefully curated collection of research, showcasing multidimensional perspectives on the intersection of neuroscience and computing. Readers can expect a deep exploration of fundamental theories, methodologies, and breakthrough applications that span the spectrum of neurocomputing. AI and Machine Learning, Deep Learning is where it is at right now. More and more academics are paying attention to it since it is a relatively young topic that has grown rapidly in the last time. In the current years, there has been a steady improvement in the presentation of CNN models on Deep Learning problems; these models are among the most significant classical structures in the field. Image classification, semantic separation, target identification, and natural language processing employ convolutional neural networks to autonomously learn sample data feature representations. A CNN model, hybrid CNN, and LSTM that incorporate text features with language knowledge may improve text language processing. | |
Разместил: Ingvar16 11-06-2025, 21:02 | Комментарии: 0 | Подробнее
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 Название: Artificial Intelligence and Machine Learning for Industry 4.0
Автор: M. Thirunavukkarasan, S.A. Sahaaya Arul Mary, Sathiyaraj. R, G.S. Pradeep Ghantasala
Издательство: Wiley-Scrivener
Год: 2025
Страниц: 322
Язык: английский
Формат: pdf (true)
Размер: 10.7 MB
This book is essential for any leader seeking to understand how to leverage intelligent automation and predictive maintenance to drive innovation, enhance productivity, and minimize downtime in their manufacturing processes. Intelligent automation is widely considered to have the greatest potential for Industry 4.0 innovations for corporations. Industrial machinery is increasingly being upgraded to intelligent machines that can perceive, act, evolve, and interact in an industrial environment. The innovative technologies featured in this machinery include the Internet of Things, cyber-physical systems, and Artificial Intelligence (AI). Artificial Intelligence enables computer systems to learn from experience, adapt to new input data, and perform intelligent tasks. Artificial Intelligence and Machine Learning for Industry 4.0 offers contemporary technological advancements in AI and Machine Learning from an Industry 4.0 perspective, looking at their prospects, obstacles, and potential applications. | |
Разместил: Ingvar16 11-06-2025, 20:05 | Комментарии: 0 | Подробнее
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 Название: Машинное обучение в Elastic Stack
Автор: Кольер Р., Монтонен К., Азарами Б.
Издательство: ДМК Пресс
Год: 2021 (2022)
Cтраниц: 380
Формат: pdf
Размер: 24 мб
Язык: русский
Elastic Stack – это комплексное решение для анализа журналов, которое помогает пользователям эффективно получать, обрабатывать и анализировать данные поиска. Книга содержит всесторонний обзор функций машинного обучения Elastic Stack (Elastic ML) как для анализа данных временных рядов, так и для классификации, регрессии и обнаружения выбросов. Концепции машинного обучения объясняются понятным и доступным языком. Рассмотрен анализ временных рядов для различных типов данных, таких как файлы журналов, сетевые потоки, показатели приложений и финансовые данные. Описано использование Elastic ML для ведения журнала, обеспечения безопасности и отслеживания показателей. После прочтения вы приобретете практический опыт совместного использования технологии машинного обучения и Elastic Stack, а также знания, необходимые для включения машинного обучения в вашу платформу распределенного поиска и анализа данных. | |
Разместил: rivasss 11-06-2025, 12:34 | Комментарии: 0 | Подробнее
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 Название: Effective Platform Engineering (MEAP v5)
Автор: Ajay Chankramath, Nic Cheneweth, Bryan Oliver, Sean Alvarez
Издательство: Manning Publications
Год: 2025
Страниц: 429
Язык: английский
Формат: pdf (true)
Размер: 23.1 MB
Learn to design and build platforms and tools that maximize developer efficiency. A great developer platform makes your development team incredibly efficient, providing a customized one-stop shop for everything they need to build and deploy applications. Effective Platform Engineering introduces platform engineering as a discipline, teaching you what goes into a great developer platform and then showing you how to develop your own. Platform engineers bridge the gap between operations and development, automating many tasks throughout the software engineering lifecycle. Effective Platform Engineering shows you how to establish and administer the kind of platforms that reduce a dev team’s workload, improve consistency, and accelerate software delivery. You’ll learn to create internal developer platforms and developer portals, as well as how to make sure your teams will use them. Effective Platform Engineering demonstrates through practical examples and scenarios how platform engineering differs from traditional DevOps, what value it brings to an organization, and how to articulate and demonstrate that value to stakeholders. For DevOps engineers familiar with Kubernetes, the cloud, and infrastructure-as-code. | |
Разместил: Ingvar16 11-06-2025, 07:52 | Комментарии: 0 | Подробнее
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