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Название: Prompt Engineering: Empowering Communication
Автор: Ajantha Devi Vairamani, Anand Nayyar
Издательство: CRC Press
Год: 2025
Страниц: 176
Язык: английский
Формат: pdf (true), epub
Размер: 13.3 MB

Prompt engineering engages as a transformative approach to enhancing interaction, creativity, and innovation. From business and healthcare to education, law, and beyond, prompt engineering is a versatile toolkit for navigating complex challenges and driving meaningful change. This book delves into the intricacies of prompt engineering, providing insights, techniques, and practical examples for leveraging prompts effectively. It explores the evolution of prompt engineering, from its early antecedents to its contemporary applications with advanced language models like ChatGPT. Readers will discover how prompts can enhance communication, foster creativity, facilitate problem-solving, and empower professionals across diverse domains. This book is your gateway to unlocking the full potential of prompt engineering. Prompts for Developers and Tech Professionals” is a comprehensive collection of prompts designed specifically for individuals working in technology and software development.

Название: AutonoML: Towards an Integrated Framework for Autonomous Machine Learning
Автор: David Jacob Kedziora, Katarzyna Musial, Bogdan Gabrys
Издательство: Now Foundations and Trends
Год выхода: 2024
Страниц: 186
Формат: PDF
Размер: 10,4 MB
Язык: английский

Over the last decade, the long-running endeavour to automate high-level processes in machine learning (ML) has risen to mainstream prominence. Beyond this, an even loftier goal is the pursuit of autonomy, which describes the capability of the system to independently adjust an ML solution over a lifetime of changing contexts. This monograph provides an expansive perspective on what constitutes an automated/autonomous ML system. In doing so, the authors survey developments in hyperparameter optimisation, multicomponent models, neural architecture search, automated feature engineering, meta-learning, multi-level ensembling, dynamic adaptation, multi-objective evaluation, resource constraints, flexible user involvement, and the principles of generalisation. Furthermore, they develop a conceptual framework throughout to illustrate one possible way of fusing high-level mechanisms into an autonomous ML system. This monograph lays the groundwork for students and researchers to understand the factors limiting architectural integration, without which the field of automated ML risks stifling both its technical advantages and general uptake.

Название: Optimization and Computing using Intelligent Data-Driven Approaches for Decision-Making: Artificial Intelligence Applications
Автор: Irfan Ali, Umar Muhammad Modibbo, Asaju La’aro Bolaji, Harish Garg
Издательство: CRC Press
Год: 2025
Страниц: 228
Язык: английский
Формат: pdf (true), epub
Размер: 13.0 MB

This book comprehensively discusses nature-inspired algorithms, Deep Learning methods, applications of mathematical programming and Artificial Intelligence techniques. It will further cover important topic such as linking green supply chain management practices with competitiveness, industry 4.0, and social responsibility. In today’s hyper‑connected digital landscape, the demand for seamless and efficient computing resources has skyrocketed, driven by the proliferation of Internet of Things (IoT) devices, edge computing, and data‑intensive applications. The convergence of fog and cloud computing has emerged as a promising solution to meet these escalating computational requirements. Fog computing, characterized by its proximity to edge devices, brings computation and data storage closer to the point of data generation, reducing latency and improving real‑time processing. Machine Learning techniques, particularly Deep Learning and Reinforcement Learning, have demonstrated remarkable capabilities in handling complex and dynamic scenarios. When combined with multi‑objective optimization approaches, they can significantly enhance load balancing in integrated fog‑cloud environments. This integration enables decision‑making processes that consider various objectives simultaneously, such as minimizing latency, maximizing energy efficiency, and ensuring resource availability.

Название: Optimization and Computing using Intelligent Data-Driven Approaches for Decision-Making: Optimization Applications
Автор: Irfan Ali, Umar Muhammad Modibbo, Asaju La’aro Bolaji, Harish Garg
Издательство: CRC Press
Год: 2025
Страниц: 335
Язык: английский
Формат: pdf (true), epub
Размер: 19.0 MB

This book comprehensively discusses nature‑inspired algorithms, deep learning methods, applications of mathematical programming, and Artificial Intelligence techniques. It further covers important topics such as the use of Machine Learning and the Internet of Things and multi‑objective optimization under Fermatean hesitant fuzzy and uncertain environment. Data Science has risen as a comprehensive field that utilizes statistical methods, data analysis, and related techniques to comprehend and scrutinize phenomena through data. Sophisticated analytics techniques, inclusive of Machine Learning models, are utilized to derive actionable intelligence or profound understanding from data. This procedure of converting raw data into significant insights is recognized as data‑driven decision‑making (DDDM). The text is primarily written for graduate students and academic researchers in diverse fields, including operations research, mathematics, statistics, Computer Science, information and communication technology, and industrial engineering.

Название: C++ & Python for Beginners - 20th Edition 2024
Автор: Papercut Limited
Издательство: Papercut Limited
Год: 2024
Язык: английский
Формат: pdf
Размер: 40.3 MB

Изучите основы Python и C++ и расширьте свои навыки программирования! Высококачественный справочник, содержащий подробные руководства от команды экспертов. Изучайте Python и применяйте его в реальных программах. Начните изучать основы C++ и лучшие советы по работе с кодом. Python и C++ - два самых мощных и многофункциональных языка программирования. Умение понимать и использовать любой из них позволит вам лучше понять современные технологии и то, как они взаимодействуют с нами и окружением.

Название: Causal Inference на Python. Причинно-следственные связи в IT-разработке
Автор: Факур Матеуш
Издательство: Спринт Бук
Год: 2025
Формат: pdf
Страниц: 400
Размер: 37,7 Мб
Язык: русский

Сколько покупателей привлечет дополнительный доллар, вложенный в онлайн-рекламу? Какие клиенты будут покупать только по скидочному купону? Как разработать оптимальную стратегию ценообразования? Причинно-следственный анализ (casual inference) — лучший способ разобраться, как влиять на бизнес-метрики, которыми вы хотите управлять. И для этого понадобится всего пара строк кода на Python. Матеуш Факур рассказывает про малоизвестные применения причинно-следственного анализа, с помощью которых можно оценить влияние воздействия на результат. Менеджеры, специалисты по работе с данными и бизнес-аналитики познакомятся как с классическими методами причинно-следственного анализа (A/B тестами, линейной регрессией, мерой склонности, синтетическим контролем, разностью разностей), так и с современными подходами (применением машинного обучения для оценки гетерогенных эффектов). Каждый метод проиллюстрирован практическим примером.

Название: Learn Data Science Using Python: A Quick-Start Guide
Автор: Engy Fouda
Издательство: Apress
Год: 2024
Страниц: 190
Язык: английский
Формат: pdf (true), epub
Размер: 14.0 MB

Harness the capabilities of Python and gain the expertise need to master Data Science techniques. This step-by-step book guides you through using Python to achieve tasks related to data cleaning, statistics, and visualization. You'll start by reviewing the foundational aspects of the Data Science process. This includes an extensive overview of research points and practical applications, such as the insightful analysis of presidential elections. The journey continues by navigating through installation procedures and providing valuable insights into Python, data types, typecasting, and essential libraries like Pandas and NumPy. You'll then delve into the captivating world of data visualization. Concepts such as scatter plots, histograms, and bubble charts come alive through detailed discussions and practical code examples, unraveling the complexities of creating compelling visualizations for enhanced data understanding. For Data Analysts, data scientists, Python programmers, and software developers new to Data Science.

Название: Optimizing Generative AI Workloads for Sustainability: Balancing Performance and Environmental Impact in Generative AI
Автор: Ishneet Kaur Dua, Parth Girish Patel
Издательство: Apress
Год: 2024
Страниц: 328
Язык: английский
Формат: pdf
Размер: 13.3 MB

This comprehensive guide provides practical strategies for optimizing Generative AI systems to be more sustainable and responsible. As advances in Generative AI such as LLMs accelerate, optimizing these resource-intensive workloads for efficiency and alignment with human values grows increasingly urgent. The book starts with the concept of Generative AI and its wide-ranging applications, while also delving into the environmental impact of AI workloads and the growing importance of adopting sustainable AI practices. It then delves into the fundamentals of efficient AI workload management, providing insights into understanding AI workload characteristics, measuring performance, and identifying bottlenecks and inefficiencies. Hardware optimization strategies are explored in detail, covering the selection of energy-efficient hardware, leveraging specialized AI accelerators, and optimizing hardware utilization and scheduling for sustainable operations. You are also guided through software optimization techniques tailored for Generative AI, including efficient model architecture, compression, and quantization methods, and optimization of software libraries and frameworks.

Название: Mastering Serverless Computing with AWS Lambda: Unlock Scalability, Optimize Costs, and Drive Innovation with AWS Lambda Serverless Solutions for Modern Cloud Transformation
Автор: Eidivandi Omid
Издательство: Orange Education Pvt Ltd
Год: 2024
Страниц: 317
Язык: английский
Формат: pdf, epub
Размер: 35.1 MB

Design and Build Scalable Solutions on the AWS Serverless Ecosystem. AWS Lambda, a key component of AWS Serverless Computing, has transformed application development by allowing developers to focus on code rather than infrastructure. Mastering Serverless Computing with AWS Lambda is a must-have guide for leveraging AWS Lambda to build efficient, cost-effective serverless cloud solutions. This book guides readers from serverless basics to advanced deployment, offering practical approaches to building resilient, scalable applications. Beginning with an introduction to serverless computing, the book explores AWS Lambda fundamentals, covering invocation models, service integrations, and event-driven design. Practical insights into hyper-scaling, instrumentation, and designing for failure empower readers to create robust, production-ready solutions. This guide covers core concepts of serverless computing, including optimizations, automation, and strategies to navigate potential pitfalls. It emphasizes AWS Lambda’s resiliency, scalability, and disaster recovery, using real-world examples to showcase best practices.

Название: Data Science Solutions on Azure: The Rise of Generative AI and Applied AI, 2nd Edition
Автор: Julian Soh, Priyanshi Singh
Издательство: Apress
Год: 2024
Страниц: 294
Язык: английский
Формат: pdf
Размер: 18.9 MB

This revamped and updated book focuses on the latest in AI technology―Generative AI. It builds on the first edition by moving away from traditional data science into the area of applied AI using the latest breakthroughs in Generative AI. Based on real-world projects, this edition takes a deep look into new concepts and approaches such as Prompt Engineering, testing and grounding of Large Language Models, fine tuning, and implementing new solution architectures such as Retrieval Augmented Generation (RAG). You will learn about new embedded AI technologies in Search, such as Semantic and Vector Search. Written with a view on how to implement Generative AI in software, this book contains examples and sample code. In addition to traditional Data Science experimentation in Azure Machine Learning (AML) that was covered in the first edition, the authors cover new tools such as Azure AI Studio, specifically for testing and experimentation with Generative AI models.