C++ Software Design
Good software design is essential for the success of your project, but designing software is hard to do. You need to have a deep understanding of the consequences of design decisions and a good overview of available design alternatives. With this book, experienced C++ developers will get a thorough, practical, and unparalleled overview of software design with this modern language. C++ trainer and consultant Klaus Iglberger explains how you can manage dependencies and abstractions, improve changeability and extensibility of software entities, and apply and implement modern design patterns to help you take advantage of today's possibilities. Software design is the most essential aspect of a software project because it impacts the software's most important properties: maintainability, changeability, and extensibility. ...
Good software design is essential for the success of your project, but designing software is hard to do. You need to have a deep understanding of the consequences of design decisions and a good overview of available design alternatives. With this book, experienced C++ developers will get a thorough, practical, and unparalleled overview of software design with this modern language. C++ trainer and consultant Klaus Iglberger explains how you can manage dependencies and abstractions, improve changeability and extensibility of software entities, and apply and implement modern design patterns to help you take advantage of today's possibilities. Software design is the most essential aspect of a software project because it impacts the software's most important properties: maintainability, changeability, and extensibility. ...
Numerical Methods Using Kotlin
This in-depth guide covers a wide range of topics, including chapters on linear algebra, root finding, curve fitting, differentiation and integration, solving differential equations, random numbers and simulation, a whole suite of unconstrained and constrained optimization algorithms, statistics, regression and time series analysis. The mathematical concepts behind the algorithms are clearly explained, with plenty of code examples and illustrations to help even beginners get started. In this book, you'll implement numerical algorithms in Kotlin using NM Dev, an object-oriented and high-performance programming library for applied and industrial mathematics. Discover how Kotlin has many advantages over Java in its speed, and in some cases, ease of use. In this book, you'll see how it can help you easily create solutions for your complex engineering and data science problems. After reading this book, you'll come away with the knowledge to create your own numerical models and algori ...
This in-depth guide covers a wide range of topics, including chapters on linear algebra, root finding, curve fitting, differentiation and integration, solving differential equations, random numbers and simulation, a whole suite of unconstrained and constrained optimization algorithms, statistics, regression and time series analysis. The mathematical concepts behind the algorithms are clearly explained, with plenty of code examples and illustrations to help even beginners get started. In this book, you'll implement numerical algorithms in Kotlin using NM Dev, an object-oriented and high-performance programming library for applied and industrial mathematics. Discover how Kotlin has many advantages over Java in its speed, and in some cases, ease of use. In this book, you'll see how it can help you easily create solutions for your complex engineering and data science problems. After reading this book, you'll come away with the knowledge to create your own numerical models and algori ...
Beginning Spring Data
Use the popular Spring Data project for data access and persistence using various Java-based APIs such as JDBC, JPA, MongoDB, and more. This book shows how to easily incorporate data persistence and accessibility into your microservices, cloud-native applications, and monolithic enterprise applications. It also teaches you how to perform unit and performance testing of a component that accesses a database. And it walks you through an example of each type of SQL and NoSQL database covered. After reading this book, you'll be able to create an application that interacts with one or multiple types of databases, and conduct unit and performance testing to analyze possible problems. ...
Use the popular Spring Data project for data access and persistence using various Java-based APIs such as JDBC, JPA, MongoDB, and more. This book shows how to easily incorporate data persistence and accessibility into your microservices, cloud-native applications, and monolithic enterprise applications. It also teaches you how to perform unit and performance testing of a component that accesses a database. And it walks you through an example of each type of SQL and NoSQL database covered. After reading this book, you'll be able to create an application that interacts with one or multiple types of databases, and conduct unit and performance testing to analyze possible problems. ...
Visual Basic .NET Notes for Professionals
The Visual Basic .NET Notes for Professionals book is compiled from Stack Overflow Documentation, the content is written by the beautiful people at Stack Overflow. ...
The Visual Basic .NET Notes for Professionals book is compiled from Stack Overflow Documentation, the content is written by the beautiful people at Stack Overflow. ...
Numerical Methods for Ordinary Differential Equations
In this book we discuss several numerical methods for solving ordinary differential equations. We emphasize the aspects that play an important role in practical problems. We con?ne ourselves to ordinary differential equations with the exception of the last chapter in which we discuss the heat equation, a parabolic partial differential equation. The techniques discussed in the intro-ductory chapters, for instance interpolation, numerical quadrature and the solution to nonlinear equations, may also be used outside the context of differential equations. They have been in-cluded to make the book self-contained as far as the numerical aspects are concerned. Chapters, sections and exercises marked with a * are not part of the Delft Institutional Package. The numerical examples in this book were implemented in Matlab, but also Python or any other programming language could be used. A list of references to background knowledge and related literature can be found at the end of this book. ...
In this book we discuss several numerical methods for solving ordinary differential equations. We emphasize the aspects that play an important role in practical problems. We con?ne ourselves to ordinary differential equations with the exception of the last chapter in which we discuss the heat equation, a parabolic partial differential equation. The techniques discussed in the intro-ductory chapters, for instance interpolation, numerical quadrature and the solution to nonlinear equations, may also be used outside the context of differential equations. They have been in-cluded to make the book self-contained as far as the numerical aspects are concerned. Chapters, sections and exercises marked with a * are not part of the Delft Institutional Package. The numerical examples in this book were implemented in Matlab, but also Python or any other programming language could be used. A list of references to background knowledge and related literature can be found at the end of this book. ...
Kubernetes Patterns, 2nd Edition
The way developers design, build, and run software has changed significantly with the evolution of microservices and containers. These modern architectures offer new distributed primitives that require a different set of practices than many developers, tech leads, and architects are accustomed to. With this focused guide, Bilgin Ibryam and Roland Huss provide common reusable patterns and principles for designing and implementing cloud native applications on Kubernetes. Each pattern includes a description of the problem and a Kubernetes-specific solution. All patterns are backed by and demonstrated with concrete code examples. This updated edition is ideal for developers and architects familiar with basic Kubernetes concepts who want to learn how to solve common cloud native challenges with proven design patterns. You'll explore: Foundational patterns covering core principles and practices for building and running container-based cloud native applications; Behavioral patterns that ...
The way developers design, build, and run software has changed significantly with the evolution of microservices and containers. These modern architectures offer new distributed primitives that require a different set of practices than many developers, tech leads, and architects are accustomed to. With this focused guide, Bilgin Ibryam and Roland Huss provide common reusable patterns and principles for designing and implementing cloud native applications on Kubernetes. Each pattern includes a description of the problem and a Kubernetes-specific solution. All patterns are backed by and demonstrated with concrete code examples. This updated edition is ideal for developers and architects familiar with basic Kubernetes concepts who want to learn how to solve common cloud native challenges with proven design patterns. You'll explore: Foundational patterns covering core principles and practices for building and running container-based cloud native applications; Behavioral patterns that ...
Machine Learning for High-Risk Applications
The past decade has witnessed the broad adoption of artificial intelligence and machine learning (AI/ML) technologies. However, a lack of oversight in their widespread implementation has resulted in some incidents and harmful outcomes that could have been avoided with proper risk management. Before we can realize AI/ML's true benefit, practitioners must understand how to mitigate its risks. This book describes approaches to responsible AI - a holistic framework for improving AI/ML technology, business processes, and cultural competencies that builds on best practices in risk management, cybersecurity, data privacy, and applied social science. Authors Patrick Hall, James Curtis, and Parul Pandey created this guide for data scientists who want to improve real-world AI/ML system outcomes for organizations, consumers, and the public. Learn technical approaches for responsible AI across explainability, model validation and debugging, bias management, data privacy, and ML security; Lea ...
The past decade has witnessed the broad adoption of artificial intelligence and machine learning (AI/ML) technologies. However, a lack of oversight in their widespread implementation has resulted in some incidents and harmful outcomes that could have been avoided with proper risk management. Before we can realize AI/ML's true benefit, practitioners must understand how to mitigate its risks. This book describes approaches to responsible AI - a holistic framework for improving AI/ML technology, business processes, and cultural competencies that builds on best practices in risk management, cybersecurity, data privacy, and applied social science. Authors Patrick Hall, James Curtis, and Parul Pandey created this guide for data scientists who want to improve real-world AI/ML system outcomes for organizations, consumers, and the public. Learn technical approaches for responsible AI across explainability, model validation and debugging, bias management, data privacy, and ML security; Lea ...
Streaming Data Mesh
Data lakes and warehouses have become increasingly fragile, costly, and difficult to maintain as data gets bigger and moves faster. Data meshes can help your organization decentralize data, giving ownership back to the engineers who produced it. This book provides a concise yet comprehensive overview of data mesh patterns for streaming and real-time data services. Authors Hubert Dulay and Stephen Mooney examine the vast differences between streaming and batch data meshes. Data engineers, architects, data product owners, and those in DevOps and MLOps roles will learn steps for implementing a streaming data mesh, from defining a data domain to building a good data product. Through the course of the book, you'll create a complete self-service data platform and devise a data governance system that enables your mesh to work seamlessly. With this book, you will: Design a streaming data mesh using Kafka; Learn how to identify a domain; Build your first data product using self-service to ...
Data lakes and warehouses have become increasingly fragile, costly, and difficult to maintain as data gets bigger and moves faster. Data meshes can help your organization decentralize data, giving ownership back to the engineers who produced it. This book provides a concise yet comprehensive overview of data mesh patterns for streaming and real-time data services. Authors Hubert Dulay and Stephen Mooney examine the vast differences between streaming and batch data meshes. Data engineers, architects, data product owners, and those in DevOps and MLOps roles will learn steps for implementing a streaming data mesh, from defining a data domain to building a good data product. Through the course of the book, you'll create a complete self-service data platform and devise a data governance system that enables your mesh to work seamlessly. With this book, you will: Design a streaming data mesh using Kafka; Learn how to identify a domain; Build your first data product using self-service to ...
Resilient Oracle PL/SQL
As legacy and other critical systems continue to migrate online, the need for continuous operation is imperative. Code has to handle data issues as well as hard external problems today, including outages of networks, storage systems, power, and ancillary systems. This practical guide provides system administrators, DevSecOps engineers, and cloud architects with a concise yet comprehensive overview on how to use PL/SQL to develop resilient database solutions. Integration specialist Stephen B Morris helps you understand the language, build a PL/SQL toolkit, and collect a suite of reusable components and patterns. You'll dive into the benefits of synthesizing the toolkit with a requirements-driven, feature-oriented approach and learn how to produce resilient solutions by synthesizing the PL/SQL toolkit in conjunction with a scale of resilience. Build solid PL/SQL solutions while avoiding common PL/SQL antipatterns; Learn why embedding complex business logic in SQL is often a brittle ...
As legacy and other critical systems continue to migrate online, the need for continuous operation is imperative. Code has to handle data issues as well as hard external problems today, including outages of networks, storage systems, power, and ancillary systems. This practical guide provides system administrators, DevSecOps engineers, and cloud architects with a concise yet comprehensive overview on how to use PL/SQL to develop resilient database solutions. Integration specialist Stephen B Morris helps you understand the language, build a PL/SQL toolkit, and collect a suite of reusable components and patterns. You'll dive into the benefits of synthesizing the toolkit with a requirements-driven, feature-oriented approach and learn how to produce resilient solutions by synthesizing the PL/SQL toolkit in conjunction with a scale of resilience. Build solid PL/SQL solutions while avoiding common PL/SQL antipatterns; Learn why embedding complex business logic in SQL is often a brittle ...
Machine Learning for Cyber Physical Systems
This open proceedings presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains selected papers from the fifth international Conference ML4CPS - Machine Learning for Cyber Physical Systems, which was held in Berlin, March 12-13, 2020. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments.The EditorsProf. Dr.-Ing. Jurgen Beyerer is Professor at the Department for Interactive Real-Time Systems at the Karlsruhe Institute of Technology. In addition he manages the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB.Dr. Alexander Maier is head of group Machine Learning at Fraunhofer IOSB-INA. His focus is on ...
This open proceedings presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains selected papers from the fifth international Conference ML4CPS - Machine Learning for Cyber Physical Systems, which was held in Berlin, March 12-13, 2020. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments.The EditorsProf. Dr.-Ing. Jurgen Beyerer is Professor at the Department for Interactive Real-Time Systems at the Karlsruhe Institute of Technology. In addition he manages the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation IOSB.Dr. Alexander Maier is head of group Machine Learning at Fraunhofer IOSB-INA. His focus is on ...