Название: AI and Microservices: Integrating AI into API Design and Distributed Microservice Architecture
Автор: Dileep Kumar Pandiya, Nilesh Charankar
Издательство: Apress
Год: 2025
Страниц: 345
Язык: английский
Формат: pdf (true), epub
Размер: 13.4 MB

This book explores how Artificial Intelligence (AI) is transforming the design and operation of microservices and API architecture. It provides a clear and practical guide to using AI to automate tasks, enhance performance, and improve the scalability of microservice-based systems. Starting with the basics, you will learn about the core concepts of microservices and API design, gradually building an understanding of how AI can be seamlessly integrated. Through real-world examples, visual diagrams, and mock APIs, the book shows you how to bring theory into practice, making complex systems easier to manage and more efficient. You will also discover strategies for testing and scaling systems, securing APIs, and addressing ethical challenges in AI-powered environments. Case studies highlight successful implementations, offering valuable insights you can apply to your own projects. For Software architects and engineers, AI and Machine Learning professionals, and DevOps engineers.

Название: Intermediate Python and Large Language Models
Автор: Dilyan Grigorov
Издательство: Apress
Год: 2025
Страниц: 342
Язык: английский
Формат: pdf (true), epub (true)
Размер: 10.1 MB

Harness the power of Large Language Models (LLMs) to build cutting-edge AI applications with Python and LangChain. This book provides a hands-on approach to understanding, implementing, and deploying LLM-powered solutions, equipping developers, data scientists, and AI enthusiasts with the tools to create real-world AI applications. The journey begins with an introduction to LangChain, covering its core concepts, integration with Python, and essential components such as prompt engineering, memory management, and retrieval-augmented generation (RAG). As you progress, you’ll explore advanced AI workflows, including multi-agent architectures, fine-tuning strategies, and optimization techniques to maximize LLM efficiency. The book also takes a deep dive into practical applications of LLMs, guiding you through the development of intelligent chatbots, document retrieval systems, content generation pipelines, and AI-driven automation tools. You’ll learn how to leverage APIs, integrate LLMs into web and mobile platforms, and optimize large-scale deployments while addressing key challenges such as inference latency, cost efficiency, and ethical considerations.

Название: How to Code Python with AI: A Beginner's Guide to Learning Coding using AI
Автор: Laurence Lars Svekis
Издательство: Independently published
Год: 2025
Страниц: 238
Язык: английский
Формат: pdf, epub, mobi
Размер: 10.1 MB

Unlock the world of Python programming with the power of artificial intelligence at your side!“How to Code Python with AI” is a revolutionary beginner’s guide that redefines how coding is learned—by teaming up with today’s most advanced AI tools like ChatGPT. Whether you're brand new to programming or have tried and struggled before, this book provides a fresh, empowering, and incredibly accessible path to mastering Python through interactive learning, hands-on practice, and AI-assisted support. Written by best-selling author and coding educator Laurence Lars Svekis, this book walks you through each foundational concept of Python programming in a simple, friendly, and visual way. Each chapter includes engaging examples, clear explanations, interactive exercises, and smart AI prompts to accelerate your learning and build your confidence. By the end of this book, you'll not only be writing Python programs with confidence but also leveraging AI as your powerful coding co-pilot. Start your journey today, and experience a whole new way to code—guided, supported, and accelerated by the intelligence of AI.

Название: Introduction to Foundation Models
Автор: Pin-Yu Chen, Sijia Liu
Издательство: Springer
Год: 2025
Страниц: 307
Язык: английский
Формат: pdf (true), epub
Размер: 42.8 MB

This book offers an extensive exploration of foundation models, guiding readers through the essential concepts and advanced topics that define this rapidly evolving research area. Designed for those seeking to deepen their understanding and contribute to the development of safer and more trustworthy AI technologies, the book is divided into three parts providing the fundamentals, advanced topics in foundation modes, and safety and trust in Foundation Models. Part I introduces the core principles of foundation models and Generative AI, presents the technical background of neural networks, delves into the learning and generalization of transformers, and finishes with the intricacies of transformers and in-context learning. Part II introduces automated visual prompting techniques, prompting LLMs with privacy, memory-efficient fine-tuning methods, and shows how LLMs can be reprogrammed for time-series Machine Learning tasks. It explores how LLMs can be reused for speech tasks, how synthetic datasets can be used to benchmark foundation models, and elucidates machine unlearning for foundation models.

Название: The AI Engineer's Guide to Surviving the EU AI ACT: Navigating the EU Regulatory Requirements
Автор: Larysa Visengeriyeva
Издательство: O’Reilly Media, Inc.
Год: 2025
Страниц: 300
Язык: английский
Формат: epub
Размер: 10.1 MB

With the introduction of the EU AI Act, companies employing AI systems face a new set of comprehensive and stringent regulations. Dr. Larysa Visengeriyeva offers a much-needed guide for navigating these unfamiliar regulatory waters to help you meet compliance challenges with confidence. From explaining the legislative framework to sharing strategies for implementing robust MLOps and data governance practices, this wide-ranging book shows you the way to thrive, not just survive, under the EU AI Act. This book also addresses the particular challenges posed by general-purpose AI (GPAI) and generative AI (GenAI), late but significant additions to the Act. The concept of generative AI operations (GenAIOps) is introduced as an extension of traditional MLOps principles to handle the unique complexities of GPAI and generative AI applications. Applying AI engineering principles to implement transparency obligations for GPAI and integrating CRISP-ML(Q), SMACTR, and GenAIOps are crucial for navigating this evolving landscape. This book is intended for AI engineers, MLOps practitioners, data scientists, AI product managers, and anyone involved in the hands-on development and deployment of AI systems.

Название: Let's Go Further. Advanced patterns for building APIs and web applications in Go
Автор: Alex Edwards
Издательство: Independently published
Год: 2025-02-21 Version 1.24.0
Страниц: 573
Язык: английский
Формат: pdf
Размер: 10.1 MB

Let’s Go Further helps you extend and expand your knowledge of Go — taking you beyond the basics and guiding you through advanced patterns for developing, managing and deploying APIs and web applications. It builds on many of the concepts that were introduced in Let’s Go, and talks through the start-to-finish build of a RESTful JSON API — from initial project setup through to deployment in production. This gives us an opportunity to cover important topics in the context of a complete, working, application — including SQL migrations, CORS requests, permission-based authorization, managing background tasks, reporting metrics, automating build and deployment steps, and much more. If you enjoyed Let’s Go, this course should be a great fit for you and an ideal next step in mastering Go.

Название: Fundamentals of Machine Learning: a Simplified Approach
Автор: Er. Sudhir Goswami, Nirvikar Katiyar, Pradeep Kumar, K.P. Sharma, Mamta Tiwari
Издательство: Blue Duck Publications
Год: 2024
Страниц: 312
Язык: английский
Формат: pdf, epub (true), mobi
Размер: 10.1 MB

This book aims to serve as a comprehensive introduction to the principles, algorithms, and applications of Machine Learning, with a particular emphasis on both foundational and cutting-edge techniques. It is designed for students, researchers, and practitioners who wish to deepen their understanding of Machine Learning concepts, explore their practical applications, and grasp the underlying mathematical frameworks. The content spans a broad range of topics, beginning with fundamental Machine Learning concepts, such as regression, decision trees, and artificial neural networks. It then delves into specialized domains like support vector machines, Reinforcement Learning, and convolutional neural networks. Along the way, readers will encounter detailed explanations of key algorithms, including ID3, Q-learning, and deep Q-learning, as well as practical insights into their implementation. Real-world case studies—such as diabetic retinopathy diagnosis using convolutional neural networks, building smart speakers, and self-driving cars—illustrate the transformative potential of these techniques.

Название: Swift подробно
Автор: Вейн Ч.
Издательство: ДМК Пресс
Год: 2020
Cтраниц: 412
Формат: pdf (ocr)
Размер: 12 мб
Язык: русский

Переходя от одной концепции к другой, эта книга знакомит вас с навыками, необходимыми для создания профессионального программного обеспечения для платформ Apple, таких как iOS и Mac, а также на сервере с Linux. Следуя многочисленным конкретным примерам, поучительным объяснениям и увлекательным упражнениям, в конечном итоге вы освоите такие мощные методы, как обобщения, эффективная обработка ошибок, протокольно-ориентированное программирование и современные шаблоны Swift.

Название: Refactoring to Rust (Final Release)
Автор: Lily Mara, Joel Holmes
Издательство: Manning Publications
Год: 2025
Страниц: 304
Язык: английский
Формат: pdf (true)
Размер: 25.7 MB

Get the speed and reliability of Rust libraries, functions, and high-performance features through incremental adoption without rewriting your codebase from scratch. Refactoring to Rust teaches you how to take advantage of Rust’s easy-to-use interoperating mechanisms. Learn practical code-mixing techniques like embedding Rust libraries into apps written in other languages. This practical guide emphasises techniques for incrementally refactoring performance-critical code to Rust while keeping the rest of your application in its original language. Refactoring to Rust teaches you to combine your favorite programming language with high-performance Rust code. Author Lily Mara introduces Rust in her easy-to-read style, clearly explaining the language's unique syntax and concepts. For intermediate programmers. No Rust experience required. This book is focused on developers who specialize in other languages, such as C, C++, Python, and jаvascript, but want to learn Rust.

Название: AI and ML for Coders in Pytorch: A Coder's Guide to Generative AI and Machine Learning (Final Release)
Автор: Laurence Moroney
Издательство: O’Reilly Media, Inc.
Год: 2025
Страниц: 529
Язык: английский
Формат: epub
Размер: 35.4 MB

Eager to learn AI and Machine Learning but unsure where to start? Laurence Moroney's hands-on, code-first guide demystifies complex AI concepts without relying on advanced mathematics. Designed for programmers, it focuses on practical applications using PyTorch, helping you build real-world models without feeling overwhelmed. From computer vision and natural language processing (NLP) to Generative AI with Hugging Face Transformers, this book equips you with the skills most in demand for AI development today. You'll also learn how to deploy your models across the web and cloud confidently. The goal of this book is to prepare you, as a coder, for just that—it’s accessible enough if you don’t fully understand ML yet, and also exposes you to the advanced concepts that will help you go deeper. The aim: to equip you to be an ML and AI developer without needing a PhD!