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Название: Ultimate AWS CDK for Infrastructure Automation: Extract the Full Potential of AWS CDK for Seamless Infrastructure Automation of Your Cloud with Practical Examples, Best Practices, and Expert Tips
Автор: Anish Kumar
Издательство: Orange Education Pvt Ltd, AVA
Год: 2025
Страниц: 278
Язык: английский
Формат: epub (true)
Размер: 10.1 MB

Transform IaC with AWS CDK to Simplify, Secure, and Scale Your Cloud. The AWS Cloud Development Kit (CDK) transforms infrastructure automation, empowering developers to simplify, optimize, and scale cloud operations. As cloud infrastructure plays a vital role in modern applications, mastering AWS CDK is a critical skill for developers and DevOps professionals. "Ultimate AWS CDK for Infrastructure Automation" equips you with practical skills to harness its full potential. This book introduces Infrastructure as Code (IaC) principles and AWS CDK fundamentals, guiding you through core concepts like stacks, constructs, environments, and resources. You'll learn to build multi-stack projects, configure CI/CD pipelines, and apply best practices for modular and reusable code. The AWS Cloud Development Kit (AWS CDK) is an open-source software development framework designed to define cloud infrastructure in code and provision it through AWS CloudFormation. Unlike traditional Infrastructure as Code (IaC) tools that use JSON or YAML, AWS CDK allows developers to use familiar high-level programming languages such as TypeScript, jаvascript, Python, Java, Go, and C#. This approach makes it easier to define cloud resources in a more expressive and programmatically rich way.

Название: Large Language Model via Rust: The State of the Art Open Foundational Models in Rust
Автор: Jaisy Malikulmulki Arasy, Evan Pradipta Hardinatha, Idham Hanif Multazam
Издательство: RantAI Academy
Год: January 6, 2025
Страниц: 133
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB

"LMVR - Large Language Models via Rust" is a pioneering open-source project that bridges the power of foundational models with the robustness of the Rust programming language. It highlights Rust's strengths in performance, safety, and concurrency while advancing the state-of-the-art in AI. Tailored for students, researchers, and professionals, LMVR delivers a comprehensive guide to building scalable, efficient, and secure large language models. By leveraging Rust, this book ensures that cutting-edge research and practical solutions go hand-in-hand. Readers will gain in-depth knowledge of model architectures, training methodologies, and real-world deployments, all while mastering Rust's unique capabilities for AI development. This book serves as a comprehensive resource for learning about large language models and their implementation in Rust. Start with Part I to build a strong foundation in the mathematical and architectural aspects of LLMs. Progress through the chapters sequentially to understand advanced transformer architectures and practical applications.

Название: Hands-On AI Trading with Python, QuantConnect, and AWS
Автор: Jiri Pik, Ernest Chan, Philip Sun, Vivek Singh, Jared Broad
Издательство: Wiley
Год: 2025
Страниц: 416
Язык: английский
Формат: True/Retail EPUB
Размер: 27.9 MB

Master the art of AI-driven algorithmic trading strategies through hands-on examples, in-depth insights, and step-by-step guidance. Hands-On AI Trading with Python, QuantConnect, and AWS explores real-world applications of AI technologies in algorithmic trading. It provides practical examples with complete code, allowing readers to understand and expand their AI toolbelt. Unlike other books, this one focuses on designing actual trading strategies rather than setting up backtesting infrastructure. It utilizes QuantConnect, providing access to key market data from Algoseek and others. Examples are available on the book's GitHub repository, written in Python, and include performance tearsheets or research Jupyter notebooks. Integrate AI into your next algorithmic trading strategy with Hands-On AI Trading with Python, QuantConnect, and AWS.

Название: Principles of Machine Learning: The Three Perspectives
Автор: Wenmin Wang
Издательство: Springer
Год: 2025
Страниц: 548
Язык: английский
Формат: pdf (true), epub
Размер: 39.5 MB

Conducting an in-depth analysis of Machine Learning, this book proposes three perspectives for studying Machine Learning: the learning frameworks, learning paradigms, and learning tasks. With this categorization, the learning frameworks reside within the theoretical perspective, the learning paradigms pertain to the methodological perspective, and the learning tasks are situated within the problematic perspective. Throughout the book, a systematic explication of Machine Learning principles from these three perspectives is provided, interspersed with some examples. This book provides a multi-dimensional and systematic interpretation of Machine Learning, rendering it suitable as a textbook reference for senior undergraduates or graduate students pursuing studies in Artificial Intelligence, Machine Learning, Data Science, Computer Science, and related disciplines. Additionally, it serves as a valuable reference for those engaged in scientific research and technical endeavors within the realm of Machine Learning.

Название: Artificial Neural Networks: Alpha Unpredictability and Chaotic Dynamics
Автор: Marat Akhmet, Madina Tleubergenova, Akylbek Zhamanshin, Zakhira Nugayeva
Издательство: Springer
Год: 2025
Страниц: 256
Язык: английский
Формат: pdf (true), epub
Размер: 52.9 MB

Mathematical chaos in neural networks is a powerful tool that reflects the world’s complexity and has the potential to uncover the mysteries of the brain’s intellectual activity. Through this monograph, the authors aim to contribute to modern chaos research, combining it with the fundamentals of classical dynamical systems and differential equations. The readers should be reassured that an in-depth understanding of chaos theory is not a prerequisite for working in the area designed by the authors. Those interested in the discussion can have a basic understanding of ordinary differential equations and the existence of bounded solutions of quasi-linear systems on the real axis. The methods and results presented in this book are meant to benefit senior researchers, engineers, and specialists working in artificial neural networks, machine and deep learning, computer science, quantum computers, and applied and pure mathematics. This broad applicability underscores the value and relevance of this research area to a large academic community and the potential impact it can have on various fields.

Название: Causal Inference for Data Science (Final Release)
Автор: Aleix Ruiz de Villa Robert
Издательство: Manning Publications
Год: 2025
Страниц: 392
Язык: английский
Формат: epub (true)
Размер: 10.1 MB

When you know the cause of an event, you can affect its outcome. This accessible introduction to causal inference shows you how to determine causality and estimate effects using statistics and Machine Learning. A/B tests or randomized controlled trials are expensive and often unfeasible in a business environment. Causal Inference for Data Science reveals the techniques and methodologies you can use to identify causes from data, even when no experiment or test has been performed. It’s possible to predict events without knowing what causes them. Understanding causality allows you both to make data-driven predictions and also intervene to affect the outcomes. Causal Inference for Data Science shows you how to build Data Science tools that can identify the root cause of trends and events. You’ll learn how to interpret historical data, understand customer behaviors, and empower management to apply optimal decisions. Why did you get a particular result? What would have lead to a different outcome? These are the essential questions of causal inference. This powerful methodology improves your decisions by connecting cause and effect—even when you can’t run experiments, A/B tests, or expensive controlled trials. For data scientists, ML engineers, and statisticians.

Название: LLM & Transformer Interview Essentials A–Z: A Silicon Valley Insider's Guide. Volume 1
Автор: X. Fang
Издательство: Independently published
Год: November 22, 2024
Страниц: 366
Язык: английский
Формат: epub
Размер: 15.3 MB

Ever since the release of ChatGPT in November 2022, the advances in AI and its growth in the public consciousness have been tremendous. At the heart of these epochal changes lies a single Machine Learning component: the transformer. Like the transistor of the 1960s, the transformer of the 2020s has given us an efficient, composable structure for solving generalized problems, and the transformer can be replicated, scaled up, modularized, and miniaturized however we might need. While the large language models (LLMs) that underpin products like ChatGPT are the most popular, these are but one configuration of the transformer. This book is written for the engineers, machine learning scientists, data scientists, and technologists who are either working with LLMs or transformers, or who are currently trying to break into the field. This technology is so new that Machine Learning interviews for such positions have not yet been standardized and commoditized to the level of LeetCode, so a broad familiarity with the core concepts is required. Indeed, it is possible to be an expert on one aspect of the LLM space yet still be blindsided by a comparatively rudimentary question on another.

Название: Обработка естественного языка с TensorFlow
Автор: Ганегедара Т.
Издательство: ДМK
Год: 2020
Cтраниц: 382
Формат: pdf (ocr)
Размер: 17 мб
Язык: русский

Обработка естественного языка применяется в различных приложениях машинного обучения, а TensorFlow является важнейшей библиотекой для реализации систем глубокого обучения на практике. Эта книга знакомит читателя с методами обработки естественного языка и содержит практическое руководство по работе с TensorFlow, предоставляя мощный инструмент для работы с огромными объемами неструктурированных данных и решения уникальных задач по обработке естественного языка.

Название: Библиотеки Python Часть 2. Практическое применение
Автор: Джейд Картер
Издательство: Литрес
Год: 2025
Формат: pdf, epub
Размер: 10 Мб
Качество: Хорошее
Язык: Русский

От анализа больших данных и машинного обучения до автоматизации рутинных процессов и создания интерактивных визуализаций — эта часть станет вашим практическим путеводителем.
Вы узнаете, как распределенно обрабатывать данные с помощью Dask и PySpark, строить динамические дашборды с Plotly и Dash, оптимизировать производительность моделей с Cython, и разрабатывать высоконагруженные приложения с использованием Asyncio и CUDA.
Кроме того, особое внимание уделено автоматизации задач, включая парсинг данных, обработку документов и создание рабочих процессов с Airflow. Визуализация геоданных, работа с изображениями и звуком, а также современные подходы к тестированию и развертыванию приложений помогут вам интегрировать Python в самые разнообразные проекты.

Название: Python for Large Language Models: A Beginners Handbook For Leveraging Llms Into Modern Development Workflows And Applications
Автор: Code Planet
Издательство: Code Planet
Год: 2025
Страниц: 292
Язык: английский
Формат: epub
Размер: 10.1 MB

Dive into the world of Large Language Models (LLMs) with this beginner-friendly guide that bridges the gap between cutting-edge AI technology and practical Python programming! Whether you're a curious coder or an aspiring AI enthusiast, this book is your gateway to mastering the art of integrating LLMs into modern development workflows and creating impactful applications. Large Language Models (LLMs) have become a cornerstone of modern Artificial Intelligence (AI), offering unprecedented capabilities in understanding, generating, and interacting with human language. These models, powered by advanced machine learning techniques, have revolutionized industries ranging from customer service to software development, and from education to creative writing. In this book, we will explore the fundamental aspects of LLMs, delving into their definition, their applications in development, and an overview of some of the most popular models, including GPT and BERT.