Abhishek Mishra Knihy

Focusing on Azure's capabilities, this book guides Java programmers through building and deploying applications on the Microsoft Azure cloud platform. It details various deployment models and offers practical examples for using Azure WebApp, Azure Kubernetes Service, Azure Functions, and Azure Spring Cloud. Additionally, it explores integration with essential components like Graph API, Azure Storage, Azure Redis Cache, and Azure SQL, providing a comprehensive resource for leveraging Azure features in Java development.

Focusing on special integrals and series sums, this book serves upper-undergraduate and graduate mathematics students. It covers differentiation and integration methods for summing series, including binomial and trigonometric series, and explores sums involving variables with fractional powers. Utilizing complex variables, it derives theorems leading to special integrals and series sums. Additionally, it discusses Bessel coefficients and functions, as well as pseudo-exponential functions. The content is structured into two parts, with problem-solving chapters complementing the theory. Prerequisites include calculus, complex analysis, and Fourier series knowledge.

The book focuses on design patterns essential for creating scalable AI solutions tailored to organizational needs. It emphasizes practical application, guiding readers through the development and deployment processes to foster innovation in intelligent automation. By leveraging these design patterns, readers can enhance their capabilities in AI project implementation, ensuring their solutions are effective and forward-thinking.

Harness the power of Apple iOS machine learning (ML) capabilities and learn the essential concepts and techniques to become a successful practitioner! Machine learning, a branch of Artificial Intelligence (AI), enables computers to act without explicit programming, providing methods to identify trends, forecast behavior, and make recommendations. The Apple iOS Software Development Kit (SDK) allows developers to integrate ML services, such as speech recognition and language translation, into mobile devices, often in multi-cloud settings. This reader-friendly guide assumes no prior experience with machine learning and offers expert instruction alongside practical examples for integrating ML into iOS applications. Organized into two sections, the book first covers fundamental ML concepts, types of ML systems, practical uses, and challenges. The second section teaches readers to use both pre-trained and user-built models with Apple's CoreML framework, providing downloadable source code examples for personal projects. Readers will gain a solid understanding of theoretical concepts and practical applications in predictive data analytics, learn to build, deploy, and maintain ML systems, and develop skills in data acquisition, modeling, classification, and regression. Additionally, the book compares traditional approaches with ML methods and explores decision tree models and integration with Scikit-learn and Keras. This resource is