Understand how to use Explainable AI (XAI) libraries and build trust in AI and machine learning models. This book utilizes a problem-solution approach to explaining machine learning models and their algorithms. The book starts with model interpretation for supervised learning linear models, which includes feature importance, partial dependency analysis, and influential data point analysis for both classification and regression models. Next, it explains supervised learning using non-linear models and state-of-the-art frameworks such as SHAP values/scores and LIME for local interpretation. Explainability for time series models is covered using LIME and SHAP, as are natural language processing-related tasks such as text classification, and sentiment analysis with ELI5, and ALIBI. The book concludes with complex model classification and regression-like neural networks and deep learning models using the CAPTUM framework that shows feature attribution, neuron attribution, and activation attribution. After reading this book, you will understand AI and machine learning models and be able to put that knowledge into practice to bring more accuracy and transparency to your analyses. What You Will Learn Create code snippets and explain machine learning models using Python Leverage deep learning models using the latest code with agile implementations Build, train, and explain neural network models designed to scale Understand the different variants of neural network models Who This Book Is For AI engineers, data scientists, and software developers interested in XAI

Unlike other resources that target only programming communities, this book targets both programming and business communities. With programming models shifting more towards no-code and low-code, citizen programmers from the business side will welcome this book as a guide for how to design and optimize their information pipeline while lowering costs for infrastructure. Programmers, on the other hand, will welcome this book's business-centric programming view, which will get them a step closer to fulfilling real business requirements. Practical Spring Cloud Function touches on the themes of portability, scalability, high performance and high availability. Each theme is explored via a real enterprise use case and code. The use cases target industries including energy (oil pipeline sensors), automotive (event-driven connected vehicles), and retail (conversational AI). After reading this book, you'll come away with the know-how to build and deploy cloud-native Java applications effectively and efficiently. What You Will Learn Write functions and deploy to Amazon Web Services, Microsoft Azure, Google Cloud, IBM Cloud, and on-prem clouds such as VMWare Tanzu and RedHat OpenShift Set up locally with KNative on Kubernetes, as well as on AWS, Azure, GCP, Tanzu, and others Build, test, and deploy a simple example with Spring Cloud Function Develop an event-driven data pipeline with Spring Cloud Function Integrate with AI and machine learning models Apply Spring Cloud Function to the Internet of Things (IoT) Get industry-specific examples of Spring Cloud Function in action Who This Book Is For Software and cloud-native application developers with prior programming experience in the cloud and/or Spring Framework. DevOps professionals may find this book beneficial as well.

This book teaches the practical implementation of various concepts for time series analysis and modeling with Python through problem-solution-style recipes, starting with data reading and preprocessing. It begins with the fundamentals of time series forecasting using statistical modeling methods like AR (autoregressive), MA (moving-average), ARMA (autoregressive moving-average), and ARIMA (autoregressive integrated moving-average). Next, you'll learn univariate and multivariate modeling using different open-sourced packages like Fbprohet, stats model, and sklearn. You'll also gain insight into classic machine learning-based regression models like randomForest, Xgboost, and LightGBM for forecasting problems. The book concludes by demonstrating the implementation of deep learning models (LSTMs and ANN) for time series forecasting. Each chapter includes several code examples and illustrations. After finishing this book, you will have a foundational understanding of various concepts relating to time series and its implementation in Python. What You Will Learn Implement various techniques in time series analysis using Python. Utilize statistical modeling methods such as AR (autoregressive), MA (moving-average), ARMA (autoregressive moving-average) and ARIMA (autoregressive integrated moving-average) for time series forecasting Understand univariate and multivariate modeling for time series forecasting Forecast using machine learning and deep learning techniques such as GBM and LSTM (long short-term memory) Who This Book Is ForData Scientists, Machine Learning Engineers, and software developers interested in time series analysis.

Get started quickly with Qt, the popular open source C++ framework for building C++-based applications and games. This book will have you building both fully functional desktop and mobile applications in no time, including some simple game applications. Introducing Qt 6 begins by guiding you in setting up your tools and environment, and then walks you through the first "baby steps" of Qt framework. Next, you'll learn the basics of how project and app structure are set up using Qt. Then, you'll begin your first real hands-on projects using Qt, including a task and problem management application and two games. As you progress, you can enhance these apps and games using additional Qt components and features. The book then delves into advanced topics in Qt, learning above and beyond what the Qt docs can offer, including local storage, C++ integration, deployment to Windows and Android, custom components and how to work with them. Upon completing this book, you'll come away knowing how to build a C++ application from design to deployment, top to bottom. And, you'll have actual application and game examples that you can apply to your own work or hobby. What You Will Learn Learn to build your first applications and games using Qt 6 framework Design, create, build and deploy your first Qt applications or games as finished products Explore local storage integration in theory and practice Cover deployment on Windows and on Android Integrate with C++ language to leverage additional functionality Dive into Custom Components and how to work with them Explore different project structures and more Who This Book Is For Software programmers, developers who are new to C++ or the Qt framework. Some prior programming experience though may be helpful.

Spring Framework 6 remains - by far - the leading de-facto "out of the box" practical Java meta application development framework for building complex enterprise, cloud-native applications as well as web applications and microservices. Introducing Spring Framework 6 is your hands-on tutorial guide for learning the Spring Framework 6 from top to bottom, and allows you to build an example application along the way from the ground-up. As you learn the Spring Framework over the course of this book, you'll incrementally build your first Spring application piece-by-piece as you learn each module, project or component of the Spring Framework and its extensions and ecosystem. As you learn the various fundamentals, you'll then apply them immediately to your Spring application. This Spring application, My Documents, enables you to learn by doing. After reading this book, you will have the essentials you should need to start using the Spring Framework and building your own Java-based applications or microservices with it. What you'll learn: Get started with Spring Framework 6 by VMWare Tanzu and the Spring community Build your first My Documents application using Spring Framework and its extensions Test your Spring application Add persistence to your application using Spring Data JPA and more Show your Spring application on the Web with Spring MVC and related Use REST APIs to enhance your application and add messaging with Kafka and AMQP Integrate your Spring application with external systems using Spring Integration toolkit Who is this book for: This book is for those aspiring software developers and programmers who are new to Spring. Some prior programming experience recommended, preferably in Java.

This book will teach you the basics of Streamlit, a Python-based application framework used to build interactive dashboards and machine learning web apps. Streamlit reduces development time for web-based application prototypes of data and machine learning models. As you'll see, Streamlit helps develop data-enhanced analytics, build dynamic user experiences, and showcases data for data science and machine learning models. Beginner's Guide to Streamlit with Python begins with the basics of Streamlit by demonstrating how to build a basic application and advances to visualization techniques and their features. Next, it covers the various aspects of a typical Streamlit web application, and explains how to manage flow control and status elements. You'll also explore performance optimization techniques necessary for data modules in a Streamlit application. Following this, you'll see how to deploy Streamlit applications on various platforms. The book concludes with a few prototype natural language processing apps with computer vision implemented using Streamlit. After reading this book, you will understand the concepts, functionalities, and performance of Streamlit, and be able to develop dynamic Streamlit web-based data and machine learning applications of your own. What You Will Learn How to start developing web applications using Streamlit What are Streamlit's components Media elements in Streamlit How to visualize data using various interactive and dynamic Python libraries How to implement models in Streamlit web applications Who This Book Is ForProfessionals working in data science and machine learning domains who want to showcase and deploy their work in a web application with no prior knowledge of web development.

Recursion is one of the most fundamental concepts in computer science and a key programming technique that allows computations to be carried out repeatedly. Despite the importance of recursion for algorithm design, most programming books do not cover the topic in detail, despite the fact that numerous computer programming professors and researchers in the field of computer science education agree that recursion is difficult for novice students. Introduction to Recursive Programming provides a detailed and comprehensive introduction to recursion. This text will serve as a useful guide for anyone who wants to learn how to think and program recursively, by analyzing a wide variety of computational problems of diverse difficulty. It contains specific chapters on the most common types of recursion (linear, tail, and multiple), as well as on algorithm design paradigms in which recursion is prevalent (divide and conquer, and backtracking). Therefore, it can be used in introductory programming courses, and in more advanced classes on algorithm design. The book also covers lower-level topics related to iteration and program execution, and includes a rich chapter on the theoretical analysis of the computational cost of recursive programs, offering readers the possibility to learn some basic mathematics along the way. It also incorporates several elements aimed at helping students master the material. First, it contains a larger collection of simple problems in order to provide a solid foundation of the core concepts, before diving into more complex material. In addition, one of the book's main assets is the use of a step-by-step methodology, together with specially designed diagrams, for guiding and illustrating the process of developing recursive algorithms. Furthermore, the book covers combinatorial problems and mutual recursion. These topics can broaden students' understanding of recursion by forcing them to apply the learned concepts differently, or in a more sophisticated manner. The code examples have been written in Python 3, but should be straightforward to understand for students with experience in other programming languages. Finally, worked out solutions to over 120 end-of-chapter exercises are available for instructors.

Build enhanced visual experiences and design and deploy modern, easy-to-maintain, client applications across a variety of platforms. This book will show you how these applications can take advantage of JavaFX's latest user interface components, 3D technology, and cloud services to create immersive visualizations and allow high-value data manipulation. The Definitive Guide to Modern Java Clients with JavaFX 17 is a professional reference for building Java applications for desktop, mobile, and embedded in the Cloud age. It offers end-to-end coverage of the latest features in JavaFX 17 and Java 17. Among the many new or updated JavaFX features covered are the FX Robot API, for simulating user interaction; customized step repeat timing for the Spinner control; Marlin FX; the ColorPicker color palette; and the GetCenter method. After reading this book, you will be equipped to upgrade legacy client applications, develop cross-platform applications in Java, and build enhanced desktop and mobile native clients. Note: source code can be downloaded from https://github.com/Apress/definitive-guide-modern-java-clients-javafx17. What You Will Learn: Create modern client applications in Java using the latest JavaFX 17 and Java 17 LTS Build enterprise clients that will enable integration with existing cloud services Use advanced visualization and 3D features Deploy on desktop, mobile, and embedded devices Who This Book Is For: Professional Java developers who are interested in learning the latest client Java development techniques to fill out their skills set.

DLP denotes a dynamic-linear modeling and optimization approach to computational decision support for resource planning problems that arise, typically, within the natural resource sciences and the disciplines of operations research and operational engineering. It integrates techniques of dynamic programming (DP) and linear programming (LP) and can be realized in an immediate, practical and usable way. Simultaneously DLP connotes a broad and very general modeling/ algorithmic concept that has numerous areas of application and possibilities for extension. Two motivating examples provide a linking thread through the main chapters, and an appendix provides a demonstration program, executable on a PC, for hands-on experience with the DLP approach.

Developed from the author's many years of teaching computing courses, Programming in C++ for Engineering and Science guides students in designing programs to solve real problems encountered in engineering and scientific applications. These problems include radioactive decay, pollution indexes, digital circuits, differential equations, Internet addresses, data analysis, simulation, quality control, electrical networks, data encryption, beam deflection, and many other areas. To make it easier for novices to develop programs, the author uses an object-centered design approach that helps students identify the objects in a problem and the operations needed; develop an algorithm for processing; implement the objects, operations, and algorithm in a program; and test, correct, and revise the program. He also revisits topics in greater detail as the text progresses. By the end of the book, students will have a solid understanding of how C++ can be used to process complex objects, including how classes can be built to model objects. Web ResourceThe book's website at http://cs.calvin.edu/books/c++/engr-sci provides source code, expanded presentations, links to relevant sites, reference materials, lab exercises, and projects. For instructors, solutions to exercises and PowerPoint slides for classroom use are available upon qualifying course adoption.

With multicore processors now in every computer, server, and embedded device, the need for cost-effective, reliable parallel software has never been greater. By explaining key aspects of multicore programming, Fundamentals of Multicore Software Development helps software engineers understand parallel programming and master the multicore challenge. Accessible to newcomers to the field, the book captures the state of the art of multicore programming in computer science. It covers the fundamentals of multicore hardware, parallel design patterns, and parallel programming in C++, .NET, and Java. It also discusses manycore computing on graphics cards and heterogeneous multicore platforms, automatic parallelization, automatic performance tuning, transactional memory, and emerging applications. As computing power increasingly comes from parallelism, software developers must embrace parallel programming. Written by leaders in the field, this book provides an overview of the existing and up-and-coming programming choices for multicores. It addresses issues in systems architecture, operating systems, languages, and compilers.

Most businesses are far more interested in accurate forecasting and fraud detection using their existing structured datasets than identifying cats in YouTube videos. Powerful deep learning techniques can efficiently extract insight from the kind of structured data collected by most businesses and organisations. Deep learning offers the potential to identify complex patterns and relationships hidden in data of all sorts. Deep Learning with Structured Data shows you how to apply powerful deep learning analysis techniques to the kind of structured, tabular data you'll find in the relational databases that real-world businesses depend on. Filled with practical, relevant applications, this book teaches you how deep learning can augment your existing machine learning and business intelligence systems. * The benefits and drawbacks of deep learning * Organizing data for your deep learning model * The deep learning stack * Measuring performance of your models For readers with an intermediate knowledge of Python, Jupyter notebooks, and machine learning.

C++ is now established as one of the leading industry programming languages for object-oriented software development. Its advantages over other languages include speed and flexibility. It is used as the base for many commercial software products and for performance solutions to complex problems. Not often taught as the primary programming language, students are frequently expected to pick up the language for themselves. This book is an ideal student self-learning guide.

As a step-by-step tutorial, this book teaches all language features and explains their practical usage. Intuitive examples are used that are neither too complex to distract, nor oversimplified. A key concept in C++ is programming with templates, which can help to program generic solutions - for example implementing polymorphism. Nicolai Josuttis teaches how to combine templates with object-oriented programming to produce the power of modern C++ development for high performance programs. It is a book that goes well beyond the basics.

A supplementary website, including source code, can be found at www.josuttis.com/cppbook

Features:

• comprehensive, detailed, readable, practical and up-to-date

• teaches how to get the power from C++, using the current ANSI language standard and programming mode

• specific hints help C and Java programmers switch and compare languages.

• website provides more examples and links to useful online resources.

Develop Android apps with Kotlin to create more elegant programs than the Java equivalent. This revised book covers the various aspects of a modern Android app that professionals are expected to encounter. You'll use the latest Kotlin APIs as made available in most recent versions of the Android SDK. There are chapters dealing with all the important aspects of the Android platform, including GUI design, file- and data-handling, coping with phone calls, multimedia apps, interaction with location and mapping services, monetizing apps, and much more. Jetpack will also be covered. It is a suite of libraries to help developers follow best practices, reduce boilerplate code, and write code that works consistently across Android versions and devices. Pro Android with Kotlin, Second Edition is an invaluable source for developers wanting to build real-world, state-of-the-art Android apps for modern Android devices using the Kotlin programming language and its APIs as available in the modern Android SDK. After reading this book, you'll come away with the skills and techniques to build modern Android apps that you can sell on Google Play. Free source code is available on this book's Github page as well. What You Will Learn Integrate activities, such as intents, services, notifications and more, into your Android apps Build UIs in Android using layouts, widgets, lists, menus, and action bars Deal with data in your Android apps using data persistence and cloud access Design for different Android devices Create multimedia apps in Android Secure, deploy, and monetize your Android apps Who This Book Is ForProfessional Android app developers.

"To the best of my knowledge, D offers an unprecedentedly adroit integration of several powerful programming paradigms: imperative, object-oriented, functional, and meta."
--From the Foreword by Walter Bright
"This is a book by a skilled author describing an interesting programming language. I'm sure you'll find the read rewarding."
--From the Foreword by Scott Meyers D is a programming language built to help programmers address the challenges of modern software development. It does so by fostering modules interconnected through precise interfaces, a federation of tightly integrated programming paradigms, language-enforced thread isolation, modular type safety, an efficient memory model, and more."The D Programming Language "is an authoritative and comprehensive introduction to D. Reflecting the author's signature style, the writing is casual and conversational, but never at the expense of focus and precision. It covers all aspects of the language (such as expressions, statements, types, functions, contracts, and modules), but it is much more than an enumeration of features.Inside the book you will findIn-depth explanations, with idiomatic examples, for all language featuresHow feature groups support major programming paradigmsRationale and best-use advice for each major featureDiscussion of cross-cutting issues, such as error handling, contract programming, and concurrencyTables, figures, and "cheat sheets" that serve as a handy quick reference for day-to-day problem solving with DWritten for the working programmer, "The D Programming Language "not only introduces the D language--it presents a compendium of good practices and idioms to help both your coding with D and your coding in general.

This book successfully balances the introduction of object-oriented concepts with data structures in C++.
KEY TOPICS: Provides interfaces for the principal example classes, which are compliant with the ANSI/ISO C++ Standard Library classes. Thorough coverage of the role of the const keyword in the C++ Standard Library. Covers C++ features such as namespaces, static member constants, typename keyword, and inheritance. Thorough review of C++ syntax and OOP concepts, make the book accessible for programmers at various levels. The book also gives readers a firm grasp of key concepts and allows programmers experienced in another language to adjust easily. A solid foundation in building and using abstract data types is also provided, along with an assortment of advanced topics such as B-trees for project building and graphs.
This book is designed for novice programmers who have learned the concepts of objects and classes and want to move on to the data structures topics of recursion and data abstraction.

Learn to program with Rust 2021 Edition, in an easy, step-by-step manner on Unix, the Linux shell, macOS, and the Windows command line. As you read this book, you'll build on the knowledge you gained in previous chapters and see what Rust has to offer. Beginning Rust starts with the basics of Rust, including how to name objects, control execution flow, and handle primitive types. You'll see how to do arithmetic, allocate memory, use iterators, and handle input/output. Once you have mastered these core skills, you'll work on handling errors and using the object-oriented features of Rust to build robust Rust applications in no time. Only a basic knowledge of programming in C or C++ and familiarity with a command console are required. After reading this book, you'll be ready to build simple Rust applications. What You Will Learn Get started programming with Rust Understand heterogeneous data structures and data sequences Define functions, generic functions, structs, and more Work with closures, changeable strings, ranges and slices Use traits and learn about lifetimes Who This Book Is For Those who are new to Rust and who have at least some prior experience with programming in general: some C/C++ is recommended particularly.

Currently, we see a variety of tools and techniques for specifying and implementing business processes. The problem is that there are still gaps and tensions between the different disciplines needed to improve business process execution and improvement in enterprises. Business process modeling, workflow execution and application programming are examples of disciplines that are hosted by different communities and that emerged separately from each other. In particular, concepts have not yet been fully elaborated at the system analysis level. Therefore, practitioners are faced again and again with similar questions in concrete business process projects: Which decomposition mechanism to use? How to find the correct granularity for business process activities? Which implementing technology is the optimal one in a given situation? This work offers an approach to the systematization of the field. The methodology used is explicitly not a comparative analysis of existing tools and techniques - although a review of existing tools is an essential basis for the considerations in the book. Rather, the book tries to provide a landscape of rationales and concepts in business processes with a discussion of alternatives.

Create and implement AI-based features in your Swift apps for iOS, macOS, tvOS, and watchOS. With this practical book, programmers and developers of all kinds will find a one-stop shop for AI and machine learning with Swift. Taking a task-based approach, you'll learn how to build features that use powerful AI features to identify images, make predictions, generate content, recommend things, and more. AI is increasingly essential for every developer-and you don't need to be a data scientist or mathematician to take advantage of it in your apps. Explore Swift-based AI and ML techniques for building applications. Learn where and how AI-driven features make sense. Inspect tools such as Apple's Python-powered Turi Create and Google's Swift for TensorFlow to train and build models. I: Fundamentals and Tools-Learn AI basics, our task-based approach, and discover how to build or find a dataset. II: Task Based AI-Build vision, audio, text, motion, and augmentation-related features; learn how to convert preexisting models. III: Beyond-Discover the theory behind task-based practice, explore AI and ML methods, and learn how you can build it all from scratch... if you want to

The latest edition of the definitive guide to the Ada language covers the full details of the core language Ada 2012 as updated by the 2016 ISO Corrigendum and introduces the key new features in Ada 2022. The book is in four parts. It begins by introducing the fundamental concepts for newcomers, before moving onto algorithmic aspects and then structural features such as OOP and multitasking. The fourth part gives details of the standard library and interaction with the external environment. Six complete executable programs illustrate the core features of the language in action. The book concludes with an appendix focussing on the new features in Ada 2022. These new features aid program proof and the efficient use of multicore architectures.

The art, craft, discipline, logic, practice and science of developing large-scale software products needs a professional base. The textbooks in this three-volume set combine informal, engineeringly sound approaches with the rigor of formal, mathematics-based approaches.

This volume covers the basic principles and techniques of specifying systems and languages. It deals with modelling the semiotics (pragmatics, semantics and syntax of systems and languages), modelling spatial and simple temporal phenomena, and such specialized topics as modularity (incl. UML class diagrams), Petri nets, live sequence charts, statecharts, and temporal logics, including the duration calculus. Finally, the book presents techniques for interpreter and compiler development of functional, imperative, modular and parallel programming languages.

This book is targeted at late undergraduate to early graduate university students, and researchers of programming methodologies. Vol. 1 of this series is a prerequisite text.

Haskell is a purely functional language that allows programmers to rapidly develop clear, concise, and correct software. The language has grown in popularity in recent years, both in teaching and in industry. This book is based on the author's experience of teaching Haskell for more than twenty years. All concepts are explained from first principles and no programming experience is required, making this book accessible to a broad spectrum of readers. While Part I focuses on basic concepts, Part II introduces the reader to more advanced topics. This new edition has been extensively updated and expanded to include recent and more advanced features of Haskell, new examples and exercises, selected solutions, and freely downloadable lecture slides and example code. The presentation is clean and simple, while also being fully compliant with the latest version of the language, including recent changes concerning applicative, monadic, foldable, and traversable types.

This Brief provides a roadmap for the R language and programming environment with signposts to further resources and documentation.