《明天》讲诉了发生在还具有一点儿古风的鲁镇上在特定的“三个晚上两白天”这个时间段的故事，故事围绕着主人公寡妇单四嫂子失去自己的儿子宝儿这个事件展开全篇的事件叙述。《明天》是鲁迅先生创作的一篇小说，这篇小说之所以叫做明天，无论站在何时说这个词，它都代表将来，非现在。无论作者或主人公，都想在摆脱现实，逃往明天。至于原因，原文斑斑可寻。全书为日文版。难词标注假名，供日语学习者学习使用。

《幸福的家庭》主要讲的是在旧社会一知识分子，为赚稿费养家糊口，于是便打算投稿写一篇符合大众口味的文章。以描写知识分子想象中的幸福家庭的模样及生活方式。知识分子虚构了一个接受了民主思想的恩爱夫妻，过着浪漫、幸福的婚姻生活。与虚构小说情节鲜明对比的是：该知识分子生活困顿，过着为三餐温饱、柴米油盐而烦恼的生活。全书为日文版。难词标注假名，供日语学习者学习使用。

《白光》是现代文学家鲁迅于1922年创作的短篇小说，作者通过讲述在科举考试中一个屡屡落第的文人陈士成，听信祖宗传言，受白光的启示在院子里挖银子未果，精神迷幻，到大山里寻宝却坠湖而死的故事，批判了封建社会病态的科考制度，揭示了十年苦读反而无用的读书人的悲惨命运。全书为日文版。难词标注假名，供日语学习者学习使用。

本故事为鲁迅创作的作品之一。村里撑船的七斤，革命时进城，被人剪去了辫子。这天他在城里的咸亨酒店听说皇帝坐了龙庭，要辫子，这消息让他烦心，更让他妻子惶恐。跟七斤有过节的赵七爷特意来恐吓七斤一家，说没了辫子就是要杀头。十多天后，七斤夫妇看出了破绽，于是七斤渐渐在村里恢复了被尊重的地位，一家的生活也回到常态。全书为日文版。难词标注假名，供日语学习者学习使用。

本故事为鲁迅创作的作品之一。这篇小说取材于女娲造人和补天的神话。小说开篇写女娲从梦中惊醒，烦闷、懊恼，自然界则是一片春回大地的绚烂景象。和风吹拂，女娲百无聊赖，心神不安，青春焕发，精力饱满而无处发泄。她走向海边，无意识捏弄软泥，于是创造了人。女娲因生命力受压抑而发挥了劳动创造精神，创造了人类，补好了崩裂的天。这是作者对封建思想意识礼教道德的勇敢挑战和彻底否定，体现了强烈的反封建精神。全书为日文版。难词标注假名，供日语学习者学习使用。

【本书内容与特点】 一、“文字?词汇”试题涉及所有的词性。 二、“语法”中的项目尽可能选择实际运用中出现比较频繁的表达形式，出题形式也努力做到紧扣真题。 三、“读解”中的文章根据考试要求以及级别的不同，选编了诸如论述文、评论文、说明文、随笔以及应用文等不同体裁的文章。文章的来源既有日本的报纸、杂志等传统出版物，也有网络、电视等媒体。 四、“听解”中的内容紧密结合实际生活，难易度和篇幅等也尽可能地接近真题，文本均由日语专家海老原博先生编写。 五、编者精心编写了所有模拟试题的详细解析及听力原文。

An Indie Next List Pick!In his first contemporary teen novel, critically acclaimed author and two-time Edgar Award finalist Lamar Giles spotlights the consequences of societal pressure, confronts toxic masculinity, and explores the complexity of what it means to be a “real man.”Del has had a crush on Kiera Westing since kindergarten. And now, during their junior year, she’s finally available. So when Kiera volunteers for an opportunity at their church, Del’s right behind her. Though he quickly realizes he’s inadvertently signed up for a Purity Pledge.His dad thinks his wires are crossed, and his best friend, Qwan, doesn’t believe any girl is worth the long game. But Del’s not about to lose his dream girl, and that’s where fellow pledger Jameer comes in. He can put in the good word. In exchange, Del just has to get answers to the Pledgers’ questions…about sex ed.With other boys circling Kiera like sharks, Del needs to make his move fast. But as he plots and plans, he neglects to ask the most important question: What does Kiera want? He can’t think about that too much, though, because once he gets the girl, it’ll all sort itself out. Right?

This thrilling YA retelling of Kurosawa’s Seven Samurai features a girl tasked with saving the world from eternal darkness. Perfect for fans of Six of Crows and Marie Lu.Seventeen-year-old Kira Fujikawa has never had it easy. She’s bullied by the popular girls in school. Her parents ignore her. And she’s also plagued with a secret: She can see yokai, the ghosts and demons that haunt the streets of Kyoto.But things accelerate from bad to worse when she learns that Shuten-doji, the demon king, will rise at the next blood moon to hunt down an ancient relic and bring the world to a catastrophic end. Not exactly skilled at fighting anything, much less the dead, Kira enlists the aid of seven powerful death gods to help her slay Shuten-doji. They include Shiro, a kitsune with boy-band looks who is more flirtatious than helpful, and O-bei, a regal demon courtier with reasons of her own for getting involved.As the confrontation with Shuten-doji draws nearer, the fate of Japan hangs in the balance. Can Kira save humankind? Or will the demon king succeed in bringing eternal darkness upon the world?

"纽约时报畅销奇幻小说《Everless》续集。《纽约时报》畅销书作者斯蒂芬妮?加伯评价《Everless》：“萨拉 ? 霍兰德是个讲故事的能手。 《Everless》赋予了‘时间不多’这个短语新的可怕意义。” 在 Sempera 王国，时间就是货币——从血液中萃取，与铁结合在一起，消耗之后可以延长寿命。 富有的贵族如格林家族，便对穷人课以重税，使自己的寿命延长了几个世纪。 十年前，女主人公朱尔斯和父亲是格林家富丽堂皇的庄园 Everless 的佣人，一场事故迫使他们在深夜逃离。 但朱尔斯发现自己的父亲寿命所剩不多，她不得不回到Everless庄园与主人做交易，以换回父亲的生命。但是回到 Everless 所带来的危险和诱惑超出了朱尔斯的想象。很快，她陷入了一场场阴谋之中，她的心也在两个人之间撕裂。这也使她下决心改变自己的命运，以及时间本身。 续集《Evermore》中，朱尔斯从小就听说过关于邪恶炼金术师和善良女巫的古老传说，而她就是那个炼金术师，她的朋友兼宿敌卡洛则是女巫。两人在过去有着几世的命运纠葛，而现在她要拼凑自己的过去来拯救现在。 The New York Times bestselling series!Jules Ember confronts the girl who is both her oldest friend and greatest enemy in the highly anticipated sequel to Everless, praised by New York Times bestelling author Stephanie Garber as “an intoxicating blend of blood, secrets, and haunting mythology.” Jules Ember was raised hearing legends of the ancient magic of the wicked Alchemist and the good Sorceress. But she has just learned the truth: She is the Alchemist, and Caro—a woman who single-handedly murdered the Queen and Jules’s first love, Roan, in cold blood—is the Sorceress.The whole kingdom believes that Jules is responsible for the murders, and a hefty bounty has been placed on her head. And Caro is intent on destroying Jules, who stole her heart twelve lifetimes ago. Now Jules must piece together the stories of her past lives to save the person who has captured her heart in this one.Perfect for fans of Victoria Aveyard, Kiera Cass, and Kendare Blake, Evermore is the high-stakes, star-crossed follow up to the New York Times bestselling Everless that fans have been waiting for.

The gripping true story of the only women to fly in combat in World War II—from Elizabeth Wein, award-winning author of Code Name VerityIn the early years of World War II, Josef Stalin issued an order that made the Soviet Union the first country in the world to allow female pilots to fly in combat. Led by Marina Raskova, these three regiments, including the 588th Night Bomber Regiment—nicknamed the “night witches”—faced intense pressure and obstacles both in the sky and on the ground. Some of these young women perished in flames. Many of them were in their teens when they went to war.This is the story of Raskova’s three regiments, women who enlisted and were deployed on the front lines of battle as navigators, pilots, and mechanics. It is the story of a thousand young women who wanted to take flight to defend their country, and the woman who brought them together in the sky.Packed with black-and-white photographs, fascinating sidebars, and thoroughly researched details, A Thousand Sisters is the inspiring true story of a group of women who set out to change the world, and the sisterhood they formed even amid the destruction of war.

A problem-solution guide to encounter various NLP tasks utilizing Java open source libraries and cloud-based solutions Key Features * Perform simple-to-complex NLP text processing tasks using modern Java libraries Extract relationships between different text complexities using a problem-solution approach * Utilize cloud-based APIs to perform machine translation operations Book Description Natural Language Processing (NLP) has become one of the prime technologies for processing very large amounts of unstructured data from disparate information sources. This book includes a wide set of recipes and quick methods that solve challenges in text syntax, semantics, and speech tasks. At the beginning of the book, you'll learn important NLP techniques, such as identifying parts of speech, tagging words, and analyzing word semantics. You will learn how to perform lexical analysis and use machine learning techniques to speed up NLP operations. With independent recipes, you will explore techniques for customizing your existing NLP engines/models using Java libraries such as OpenNLP and the Stanford NLP library. You will also learn how to use NLP processing features from cloud-based sources, including Google and Amazon’s AWS. You will master core tasks, such as stemming, lemmatization, part-of-speech tagging, and named entity recognition. You will also learn about sentiment analysis, semantic text similarity, language identification, machine translation, and text summarization. By the end of this book, you will be ready to become a professional NLP expert using a problem-solution approach to analyze any sort of text, sentences, or semantic words. What you will learn * Explore how to use tokenizers in NLP processing * Implement NLP techniques in machine learning and deep learning applications * Identify sentences within the text and learn how to train specialized NER models * Learn how to classify documents and perform sentiment analysis * Find semantic similarities between text elements and extract text from a variety of sources * Preprocess text from a variety of data sources * Learn how to identify and translate languages Who this book is for This book is for data scientists, NLP engineers, and machine learning developers who want to perform their work on linguistic applications faster with the use of popular libraries on JVM machines. This book will help you build real-world NLP applications using a recipe-based approach. Prior knowledge of Natural Language Processing basics and Java programming is expected.

Develop generative models for a variety of real-world use-cases and deploy them to production Key Features * Discover various GAN architectures using Python and Keras library * Understand how GAN models function with the help of theoretical and practical examples * Apply your learnings to become an active contributor to open source GAN applications Book Description Generative Adversarial Networks (GANs) have revolutionized the fields of machine learning and deep learning. This book will be your first step towards understanding GAN architectures and tackling the challenges involved in training them. This book opens with an introduction to deep learning and generative models, and their applications in artificial intelligence (AI). You will then learn how to build, evaluate, and improve your first GAN with the help of easy-to-follow examples. The next few chapters will guide you through training a GAN model to produce and improve high-resolution images. You will also learn how to implement conditional GANs that give you the ability to control characteristics of GAN outputs. You will build on your knowledge further by exploring a new training methodology for progressive growing of GANs. Moving on, you'll gain insights into state-of-the-art models in image synthesis, speech enhancement, and natural language generation using GANs. In addition to this, you'll be able to identify GAN samples with TequilaGAN. By the end of this book, you will be well-versed with the latest advancements in the GAN framework using various examples and datasets, and you will have the skills you need to implement GAN architectures for several tasks and domains, including computer vision, natural language processing (NLP), and audio processing. Foreword by Ting-Chun Wang, Senior Research Scientist, NVIDIA What you will learn * Learn how GANs work and the advantages and challenges of working with them * Control the output of GANs with the help of conditional GANs, using embedding and space manipulation * Apply GANs to computer vision, NLP, and audio processing * Understand how to implement progressive growing of GANs * Use GANs for image synthesis and speech enhancement * Explore the future of GANs in visual and sonic arts * Implement pix2pixHD to turn semantic label maps into photorealistic images Who this book is for This book is for machine learning practitioners, deep learning researchers, and AI enthusiasts who are looking for a perfect mix of theory and hands-on content in order to implement GANs using Keras. Working knowledge of Python is expected.

Discover interesting recipes to help you understand the concepts of object detection, image processing, and facial detection Key Features * Explore the latest features and APIs in OpenCV 4 and build computer vision algorithms * Develop effective, robust, and fail-safe vision for your applications * Build computer vision algorithms with machine learning capabilities Book Description OpenCV is an image and video processing library used for all types of image and video analysis. Throughout the book, you'll work through recipes that implement a variety of tasks, such as facial recognition and detection. With 70 self-contained tutorials, this book examines common pain points and best practices for computer vision (CV) developers. Each recipe addresses a specific problem and offers a proven, best-practice solution with insights into how it works, so that you can copy the code and configuration files and modify them to suit your needs. This book begins by setting up OpenCV, and explains how to manipulate pixels. You'll understand how you can process images with classes and count pixels with histograms. You'll also learn detecting, describing, and matching interest points. As you advance through the chapters, you'll get to grips with estimating projective relations in images, reconstructing 3D scenes, processing video sequences, and tracking visual motion. In the final chapters, you'll cover deep learning concepts such as face and object detection. By the end of the book, you'll be able to confidently implement a range to computer vision algorithms to meet the technical requirements of your complex CV projects What you will learn * Install and create a program using the OpenCV library * Segment images into homogenous regions and extract meaningful objects * Apply image filters to enhance image content * Exploit image geometry to relay different views of a pictured scene * Calibrate the camera from different image observations * Detect people and objects in images using machine learning techniques * Reconstruct a 3D scene from images * Explore face detection using deep learning Who this book is for If you’re a CV developer or professional who already uses or would like to use OpenCV for building computer vision software, this book is for you. You’ll also find this book useful if you’re a C++ programmer looking to extend your computer vision skillset by learning OpenCV.

A comprehensive guide to programming with network sockets, implementing Internet protocols, designing IoT devices, and much more with C Key Features * Leverage your C or C++ programming skills to build powerful network applications * Get to grips with a variety of network protocols that allow you to load web pages, send emails, and do much more * Write portable network code for operating systems such as Windows, Linux, and macOS Book Description Network programming, a challenging topic in C, is made easy to understand with a careful exposition of socket programming APIs. This book gets you started with modern network programming in C and the right use of relevant operating system APIs. This book covers core concepts, such as hostname resolution with DNS, that are crucial to the functioning of the modern web. You’ll delve into the fundamental network protocols, TCP and UDP. Essential techniques for networking paradigms such as client-server and peer-to-peer models are explained with the help of practical examples. You’ll also study HTTP and HTTPS (the protocols responsible for web pages) from both the client and server perspective. To keep up with current trends, you’ll apply the concepts covered in this book to gain insights into web programming for IoT. You’ll even get to grips with network monitoring and implementing security best practices. By the end of this book, you’ll have experience of working with client-server applications, and be able to implement new network programs in C. The code in this book is compatible with the older C99 version as well as the latest C18 and C++17 standards. Special consideration is given to writing robust, reliable, and secure code that is portable across operating systems, including Winsock sockets for Windows and POSIX sockets for Linux and macOS. What you will learn * Uncover cross-platform socket programming APIs * Implement techniques for supporting IPv4 and IPv6 * Understand how TCP and UDP connections work over IP * Discover how hostname resolution and DNS work * Interface with web APIs using HTTP and HTTPS * Acquire hands-on experience with Simple Mail Transfer Protocol (SMTP) * Apply network programming to the Internet of Things (IoT) Who this book is for If you're a developer or a system administrator who wants to enter the world of network programming, this book is for you. Basic knowledge of C programming is assumed.

Learn dynamic programming with Julia to build apps for data analysis, visualization, machine learning, and the web Key Features * Leverage Julia's high speed and efficiency to build fast, efficient applications * Perform supervised and unsupervised machine learning and time series analysis * Tackle problems concurrently and in a distributed environment Book Description Julia offers the high productivity and ease of use of Python and R with the lightning-fast speed of C++. There’s never been a better time to learn this language, thanks to its large-scale adoption across a wide range of domains, including fintech, biotech and artificial intelligence (AI). You will begin by learning how to set up a running Julia platform, before exploring its various built-in types. This Learning Path walks you through two important collection types: arrays and matrices. You’ll be taken through how type conversions and promotions work, and in further chapters you'll study how Julia interacts with operating systems and other languages. You’ll also learn about the use of macros, what makes Julia suitable for numerical and scientific computing, and how to run external programs. Once you have grasped the basics, this Learning Path goes on to how to analyze the Iris dataset using DataFrames. While building a web scraper and a web app, you’ll explore the use of functions, methods, and multiple dispatches. In the final chapters, you'll delve into machine learning, where you'll build a book recommender system. By the end of this Learning Path, you’ll be well versed with Julia and have the skills you need to leverage its high speed and efficiency for your applications. This Learning Path includes content from the following Packt products: * Julia 1.0 Programming - Second Edition by Ivo Balbaert * Julia Programming Projects by Adrian Salceanu What you will learn * Create your own types to extend the built-in type system * Visualize your data in Julia with plotting packages * Explore the use of built-in macros for testing and debugging * Integrate Julia with other languages such as C, Python, and MATLAB * Analyze and manipulate datasets using Julia and DataFrames * Develop and run a web app using Julia and the HTTP package * Build a recommendation system using supervised machine learning Who this book is for If you are a statistician or data scientist who wants a quick course in the Julia programming language while building big data applications, this Learning Path is for you. Basic knowledge of mathematics and programming is a must.

Leverage the power of Python and statistical modeling techniques for building accurate predictive models Key Features * Get introduced to Python's rich suite of libraries for statistical modeling * Implement regression, clustering and train neural networks from scratch * Includes real-world examples on training end-to-end machine learning systems in Python Book Description Python's ease of use and multi-purpose nature has led it to become the choice of tool for many data scientists and machine learning developers today. Its rich libraries are widely used for data analysis, and more importantly, for building state-of-the-art predictive models. This book takes you through an exciting journey, of using these libraries to implement effective statistical models for predictive analytics. You’ll start by diving into classical statistical analysis, where you will learn to compute descriptive statistics using pandas. You will look at supervised learning, where you will explore the principles of machine learning and train different machine learning models from scratch. You will also work with binary prediction models, such as data classification using k-nearest neighbors, decision trees, and random forests. This book also covers algorithms for regression analysis, such as ridge and lasso regression, and their implementation in Python. You will also learn how neural networks can be trained and deployed for more accurate predictions, and which Python libraries can be used to implement them. By the end of this book, you will have all the knowledge you need to design, build, and deploy enterprise-grade statistical models for machine learning using Python and its rich ecosystem of libraries for predictive analytics. What you will learn * Understand the importance of statistical modeling * Learn about the various Python packages for statistical analysis * Implement algorithms such as Naive Bayes, random forests, and more * Build predictive models from scratch using Python's scikit-learn library * Implement regression analysis and clustering * Learn how to train a neural network in Python Who this book is for If you are a data scientist, a statistician or a machine learning developer looking to train and deploy effective machine learning models using popular statistical techniques, then this book is for you. Knowledge of Python programming is required to get the most out of this book.

Design and implement professional-level programs by leveraging modern data structures and algorithms in Rust Key Features * Improve your productivity by writing more simple and easy code in Rust * Discover the functional and reactive implementations of traditional data structures * Delve into new domains of Rust, including WebAssembly, networking, and command-line tools Book Description Rust is a powerful language with a rare combination of safety, speed, and zero-cost abstractions. This Learning Path is filled with clear and simple explanations of its features along with real-world examples, demonstrating how you can build robust, scalable, and reliable programs. You’ll get started with an introduction to Rust data structures, algorithms, and essential language constructs. Next, you will understand how to store data using linked lists, arrays, stacks, and queues. You’ll also learn to implement sorting and searching algorithms, such as Brute Force algorithms, Greedy algorithms, Dynamic Programming, and Backtracking. As you progress, you’ll pick up on using Rust for systems programming, network programming, and the web. You’ll then move on to discover a variety of techniques, right from writing memory-safe code, to building idiomatic Rust libraries, and even advanced macros. By the end of this Learning Path, you’ll be able to implement Rust for enterprise projects, writing better tests and documentation, designing for performance, and creating idiomatic Rust code. This Learning Path includes content from the following Packt products: * Mastering Rust - Second Edition by Rahul Sharma and Vesa Kaihlavirta * Hands-On Data Structures and Algorithms with Rust by Claus Matzinger What you will learn * Design and implement complex data structures in Rust * Create and use well-tested and reusable components with Rust * Understand the basics of multithreaded programming and advanced algorithm design * Explore application profiling based on benchmarking and testing * Study and apply best practices and strategies in error handling * Create efficient web applications with the Actix-web framework * Use Diesel for type-safe database interactions in your web application Who this book is for If you are already familiar with an imperative language and now want to progress from being a beginner to an intermediate-level Rust programmer, this Learning Path is for you. Developers who are already familiar with Rust and want to delve deeper into the essential data structures and algorithms in Rust will also find this Learning Path useful.

Teach your machine to think for itself! Key Features * Delve into supervised learning and grasp how a machine learns from data * Implement popular machine learning algorithms from scratch, developing a deep understanding along the way * Explore some of the most popular scientific and mathematical libraries in the Python language Book Description Supervised machine learning is used in a wide range of sectors (such as finance, online advertising, and analytics) because it allows you to train your system to make pricing predictions, campaign adjustments, customer recommendations, and much more while the system self-adjusts and makes decisions on its own. As a result, it's crucial to know how a machine “learns” under the hood. This book will guide you through the implementation and nuances of many popular supervised machine learning algorithms while facilitating a deep understanding along the way. You’ll embark on this journey with a quick overview and see how supervised machine learning differs from unsupervised learning. Next, we explore parametric models such as linear and logistic regression, non-parametric methods such as decision trees, and various clustering techniques to facilitate decision-making and predictions. As we proceed, you'll work hands-on with recommender systems, which are widely used by online companies to increase user interaction and enrich shopping potential. Finally, you’ll wrap up with a brief foray into neural networks and transfer learning. By the end of this book, you’ll be equipped with hands-on techniques and will have gained the practical know-how you need to quickly and powerfully apply algorithms to new problems. What you will learn * Crack how a machine learns a concept and generalize its understanding to new data * Uncover the fundamental differences between parametric and non-parametric models * Implement and grok several well-known supervised learning algorithms from scratch * Work with models in domains such as ecommerce and marketing * Expand your expertise and use various algorithms such as regression, decision trees, and clustering * Build your own models capable of making predictions * Delve into the most popular approaches in deep learning such as transfer learning and neural networks Who this book is for This book is for aspiring machine learning developers who want to get started with supervised learning. Intermediate knowledge of Python programming—and some fundamental knowledge of supervised learning—are expected.

Delve into the world of Kotlin and learn to build powerful Android and web applications Key Features * Learn the fundamentals of Kotlin to write high-quality code * Test and debug your applications with the different unit testing frameworks in Kotlin * Explore Kotlin's interesting features such as null safety, reflection, and annotations Book Description Kotlin is a general-purpose programming language used for developing cross-platform applications. Complete with a comprehensive introduction and projects covering the full set of Kotlin programming features, this book will take you through the fundamentals of Kotlin and get you up to speed in no time. Learn Kotlin Programming covers the installation, tools, and how to write basic programs in Kotlin. You'll learn how to implement object-oriented programming in Kotlin and easily reuse your program or parts of it. The book explains DSL construction, serialization, null safety aspects, and type parameterization to help you build robust apps. You'll learn how to destructure expressions and write your own. You'll then get to grips with building scalable apps by exploring advanced topics such as testing, concurrency, microservices, coroutines, and Kotlin DSL builders. Furthermore, you'll be introduced to the kotlinx.serialization framework, which is used to persist objects in JSON, Protobuf, and other formats. By the end of this book, you'll be well versed with all the new features in Kotlin and will be able to build robust applications skillfully. What you will learn * Explore the latest Kotlin features in order to write structured and readable object-oriented code * Get to grips with using lambdas and higher-order functions * Write unit tests and integrate Kotlin with Java code * Create real-world apps in Kotlin in the microservices style * Use Kotlin extensions with the Java collections library * Uncover destructuring expressions and find out how to write your own * Understand how Java-nullable code can be integrated with Kotlin features Who this book is for If you’re a beginner or intermediate programmer who wants to learn Kotlin to build applications, this book is for you. You’ll also find this book useful if you’re a Java developer interested in switching to Kotlin.

Take your SAP ABAP skills to the next level by mastering ABAP programming techniques with the help of real-world examples Key Features * Become adept at building interfaces and explore ABAP tools and techniques * Discover the modern functionalities available in the latest version of ABAP * Learn the process of creating stunning HTML5 applications using SAPUI5 Book Description Advanced Business Application Programming (ABAP) is an established and complex programming language in the IT industry. This book is designed to help you use the latest ABAP techniques and apply legacy constructions using practical examples. You'll start with a quick refresher on language and database concepts, followed by agile techniques for adding custom code to a modern ABAP system. After this, you will get up to speed with the complete ABAP toolset for importing data to and from different environments. Next, you'll learn how to print forms and work with the different ABAP tools for Extensible Markup Language (XML) manipulation. While covering further chapters, you'll gain insights into building stunning UI5 interfaces, in addition to learning how to develop simple apps using the Business Object Processing Framework (BOPF). You will also pick up the technique of handling exceptions and performing testing in ABAP. In the concluding chapters, you can look forward to grasping various techniques for optimizing the performance of programs using a variety of performance analysis tools. By the end of this book, you will have the expertise you need to confidently build maintainable programs in Systems, Applications, and Products (SAP). What you will learn * Create stable and error-free ABAP programs * Leverage new ABAP concepts including object-oriented programming(OOP) and Model-View-Controller (MVC) * Learn to add custom code to your existing SAP program * Speed up your ABAP programs by spotting bottlenecks * Understand techniques such as performance tuning and optimization * Develop modern and beautiful user interfaces (UIs) in an ABAP environment * Build multiple classes with any nesting level Who this book is for This book is for developers who want to learn and use ABAP skills to become an industry expert. Familiarity with object-oriented programming concepts is expected.

Manage Microsoft Azure cloud services that span storage, security, networking, and compute cloud capabilities and ace the AZ-103 Exam Key Features * Master features and concepts pertaining to Azure's Administration services * Gain a deep understanding of various Azure services related to infrastructure, applications, and environments * Gauge yourself by giving mock tests with up-to-date exam questions Book Description Microsoft Azure Administrator – Exam Guide AZ-103 will cover all the exam objectives that will help you earn Microsoft Azure Administrator certification. Whether you want to clear AZ-103 exam or want hands-on experience in administering Azure, this study guide will help you achieve your objective. It covers the latest features and capabilities around configuring, managing, and securing Azure resources. Following Microsoft's AZ-103 exam syllabus, this guide is divided into five modules. The first module talks about how to manage Azure subscriptions and resources. You will be able to configure Azure subscription policies at Azure subscription level and learn how to use Azure policies for resource groups. Later, the book covers techniques related to implementing and managing storage in Azure. You will be able to create and configure backup policies and perform restore operations. The next module will guide you to create, configure, and deploy virtual machines for Windows and Linux. In the last two modules, you will learn about configuring and managing virtual networks and managing identities. The book concludes with effective mock tests along with answers so that you can confidently crack this exam. By the end of this book, you will acquire the skills needed to pass Exam AZ-103. What you will learn * Configure Azure subscription policies and manage resource groups * Monitor activity log by using Log Analytics * Modify and deploy Azure Resource Manager (ARM) templates * Protect your data with Azure Site Recovery * Learn how to manage identities in Azure * Monitor and troubleshoot virtual network connectivity * Manage Azure Active Directory Connect, password sync, and password writeback Who this book is for This book is for Azure administrators, systems administrators or anyone preparing for AZ 103 exam and wants to master Azure's various administration features. Readers should have proficiency in working with PowerShell, CLI and other day-to-day Azure administration tasks.