Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and Keras Key Features *Implement machine learning algorithms to build, train, and validate algorithmic models *Create your own algorithmic design process to apply probabilistic machine learning approaches to trading decisions *Develop neural networks for algorithmic trading to perform time series forecasting and smart analytics Book Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This book enables you to use a broad range of supervised and unsupervised algorithms to extract signals from a wide variety of data sources and create powerful investment strategies. This book shows how to access market, fundamental, and alternative data via API or web scraping and offers a framework to evaluate alternative data. You’ll practice the ML work?ow from model design, loss metric definition, and parameter tuning to performance evaluation in a time series context. You will understand ML algorithms such as Bayesian and ensemble methods and manifold learning, and will know how to train and tune these models using pandas, statsmodels, sklearn, PyMC3, xgboost, lightgbm, and catboost. This book also teaches you how to extract features from text data using spaCy, classify news and assign sentiment scores, and to use gensim to model topics and learn word embeddings from financial reports. You will also build and evaluate neural networks, including RNNs and CNNs, using Keras and PyTorch to exploit unstructured data for sophisticated strategies. Finally, you will apply transfer learning to satellite images to predict economic activity and use reinforcement learning to build agents that learn to trade in the OpenAI Gym. What you will learn *Implement machine learning techniques to solve investment and trading problems *Leverage market, fundamental, and alternative data to research alpha factors *Design and fine-tune supervised, unsupervised, and reinforcement learning models *Optimize portfolio risk and performance using pandas, NumPy, and scikit-learn *Integrate machine learning models into a live trading strategy on Quantopian *Evaluate strategies using reliable backtesting methodologies for time series *Design and evaluate deep neural networks using Keras, PyTorch, and TensorFlow *Work with reinforcement learning for trading strategies in the OpenAI Gym Who this book is for Hands-On Machine Learning for Algorithmic Trading is for data analysts, data scientists, and Python developers, as well as investment analysts and portfolio managers working within the finance and investment industry. If you want to perform efficient algorithmic trading by developing smart investigating strategies using machine learning algorithms, this is the book for you. Some understanding of Python and machine learning techniques is mandatory.

Explore a diverse set of meta-learning algorithms and techniques to enable human-like cognition for your machine learning models using various Python frameworks Key Features *Understand the foundations of meta learning algorithms *Explore practical examples to explore various one-shot learning algorithms with its applications in TensorFlow *Master state of the art meta learning algorithms like MAML, reptile, meta SGD Book Description Meta learning is an exciting research trend in machine learning, which enables a model to understand the learning process. Unlike other ML paradigms, with meta learning you can learn from small datasets faster. Hands-On Meta Learning with Python starts by explaining the fundamentals of meta learning and helps you understand the concept of learning to learn. You will delve into various one-shot learning algorithms, like siamese, prototypical, relation and memory-augmented networks by implementing them in TensorFlow and Keras. As you make your way through the book, you will dive into state-of-the-art meta learning algorithms such as MAML, Reptile, and CAML. You will then explore how to learn quickly with Meta-SGD and discover how you can perform unsupervised learning using meta learning with CACTUs. In the concluding chapters, you will work through recent trends in meta learning such as adversarial meta learning, task agnostic meta learning, and meta imitation learning. By the end of this book, you will be familiar with state-of-the-art meta learning algorithms and able to enable human-like cognition for your machine learning models. What you will learn *Understand the basics of meta learning methods, algorithms, and types *Build voice and face recognition models using a siamese network *Learn the prototypical network along with its variants *Build relation networks and matching networks from scratch *Implement MAML and Reptile algorithms from scratch in Python *Work through imitation learning and adversarial meta learning *Explore task agnostic meta learning and deep meta learning Who this book is for Hands-On Meta Learning with Python is for machine learning enthusiasts, AI researchers, and data scientists who want to explore meta learning as an advanced approach for training machine learning models. Working knowledge of machine learning concepts and Python programming is necessary.

Speed up the design and implementation of deep learning solutions using Apache Spark Key Features * Explore the world of distributed deep learning with Apache Spark * Train neural networks with deep learning libraries such as BigDL and TensorFlow * Develop Spark deep learning applications to intelligently handle large and complex datasets Book Description Deep learning is a subset of machine learning where datasets with several layers of complexity can be processed. Hands-On Deep Learning with Apache Spark addresses the sheer complexity of technical and analytical parts and the speed at which deep learning solutions can be implemented on Apache Spark. The book starts with the fundamentals of Apache Spark and deep learning. You will set up Spark for deep learning, learn principles of distributed modeling, and understand different types of neural nets. You will then implement deep learning models, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) on Spark. As you progress through the book, you will gain hands-on experience of what it takes to understand the complex datasets you are dealing with. During the course of this book, you will use popular deep learning frameworks, such as TensorFlow, Deeplearning4j, and Keras to train your distributed models. By the end of this book, you'll have gained experience with the implementation of your models on a variety of use cases. What you will learn * Understand the basics of deep learning * Set up Apache Spark for deep learning * Understand the principles of distribution modeling and different types of neural networks * Obtain an understanding of deep learning algorithms * Discover textual analysis and deep learning with Spark * Use popular deep learning frameworks, such as Deeplearning4j, TensorFlow, and Keras * Explore popular deep learning algorithms Who this book is for If you are a Scala developer, data scientist, or data analyst who wants to learn how to use Spark for implementing efficient deep learning models, Hands-On Deep Learning with Apache Spark is for you. Knowledge of the core machine learning concepts and some exposure to Spark will be helpful.

Implement defensive techniques in your ecosystem successfully with Python Key Features * Identify and expose vulnerabilities in your infrastructure with Python * Learn custom exploit development . * Make robust and powerful cybersecurity tools with Python Book Description With the current technological and infrastructural shift, penetration testing is no longer a process-oriented activity. Modern-day penetration testing demands lots of automation and innovation; the only language that dominates all its peers is Python. Given the huge number of tools written in Python, and its popularity in the penetration testing space, this language has always been the first choice for penetration testers. Hands-On Penetration Testing with Python walks you through advanced Python programming constructs. Once you are familiar with the core concepts, you’ll explore the advanced uses of Python in the domain of penetration testing and optimization. You’ll then move on to understanding how Python, data science, and the cybersecurity ecosystem communicate with one another. In the concluding chapters, you’ll study exploit development, reverse engineering, and cybersecurity use cases that can be automated with Python. By the end of this book, you’ll have acquired adequate skills to leverage Python as a helpful tool to pentest and secure infrastructure, while also creating your own custom exploits. What you will learn * Get to grips with Custom vulnerability scanner development * Familiarize yourself with web application scanning automation and exploit development * Walk through day-to-day cybersecurity scenarios that can be automated with Python * Discover enterprise-or organization-specific use cases and threat-hunting automation * Understand reverse engineering, fuzzing, buffer overflows , key-logger development, and exploit development for buffer overflows. * Understand web scraping in Python and use it for processing web responses * Explore Security Operations Centre (SOC) use cases * Get to understand Data Science, Python, and cybersecurity all under one hood Who this book is for If you are a security consultant , developer or a cyber security enthusiast with little or no knowledge of Python and want in-depth insight into how the pen-testing ecosystem and python combine to create offensive tools , exploits , automate cyber security use-cases and much more then this book is for you. Hands-On Penetration Testing with Python guides you through the advanced uses of Python for cybersecurity and pen-testing, helping you to better understand security loopholes within your infrastructure .

Explore powerful Azure DevOps solutions to develop and deploy your software faster and more efficiently. Key Features * Build modern microservice-based systems with Azure architecture * Learn to deploy and manage cloud services and virtual machines * Configure clusters with Azure Service Fabric for deployment Book Description This Learning Path helps you understand microservices architecture and leverage various services of Microsoft Azure Service Fabric to build, deploy, and maintain highly scalable enterprise-grade applications. You will learn to select an appropriate Azure backend structure for your solutions and work with its toolkit and managed apps to share your solutions with its service catalog. As you progress through the Learning Path, you will study Azure Cloud Services, Azure-managed Kubernetes, and Azure Container Services deployment techniques. To apply all that you’ve understood, you will build an end-to-end Azure system in scalable, decoupled tiers for an industrial bakery with three business domains. Toward the end of this Learning Path, you will build another scalable architecture using Azure Service Bus topics to send orders between decoupled business domains with scalable worker roles processing these orders. By the end of this Learning Path, you will be comfortable in using development, deployment, and maintenance processes to build robust cloud solutions on Azure. This Learning Path includes content from the following Packt products: * Learn Microsoft Azure by Mohamed Wali * Implementing Azure Solutions - Second Edition by Florian Klaffenbach, Oliver Michalski, Markus Klein * Microservices with Azure by Namit Tanasseri and Rahul Rai What you will learn * Study various Azure Service Fabric application programming models * Create and manage a Kubernetes cluster in Azure Kubernetes Service * Use site-to-site VPN and ExpressRoute connections in your environment * Design an Azure IoT app and learn to operate it in various scenarios * Implement a hybrid Azure design using Azure Stack * Build Azure SQL databases with Code First Migrations * Integrate client applications with Web API and SignalR on Azure * Implement the Azure Active Directory (Azure AD) across the entire system Who this book is for If you are an IT system architect, network admin, or a DevOps engineer who wants to implement Azure solutions for your organization, this Learning Path is for you. Basic knowledge of the Azure Cloud platform will be beneficial.

Get ready for the Windows 10: 70-698 exam and configure Windows to manage data recovery Key Features * Implement Windows 10 operational and administrative tasks * Configure devices, remote management settings, advanced management tools, and device drivers * Comprehensive guide to help you work efficiently in Windows 10 Book Description The Installing and Configuring Windows 10: 70-698 Exam Guide is designed to confirm what you already know, while also updating your knowledge of Windows 10. With its easy-to-follow guidance, you will quickly learn the user interface and discover steps to work efficiently in Windows 10 to rule out delays and obstacles. This book begins by covering various ways of installing Windows 10, followed by instructions on post-installation tasks. You will learn about the deployment of Windows 10 in Enterprise and also see how to configure networking in Windows 10. You’ll understand how to leverage Disk Management and Windows PowerShell to configure disks, volumes, and file system options. As you progress through the chapters, you will be able to set up remote management in Windows 10 and learn more about Windows update usage, behavior, and settings. You will also gain insights that will help you monitor and manage data recovery and explore how to configure authentication, authorization, and advanced management tools in Windows 10. By the end of this book, you will be equipped with enough knowledge to take the 70-698 exam and explore different study methods to improve your chances of passing the exam with ease. What you will learn * Discover various ways of installing Windows 10 * Understand how to configure devices and device drivers * Configure and support IPv4 and IPv6 network settings * Troubleshoot storage and removable device issues * Get to grips with data access and usage * Explore the advanced management tools available in Windows 10 Who this book is for This book is for IT professionals who perform installation, configuration, general local management and maintenance of Windows 10 core services and are preparing to clear the Windows 10: 70-698 exam

The second book in New York Times bestselling author and National Book Award finalist Eliot Schrefer’s Lost Rainforest series will thrill fans of Warriors and Spirit Animals with action and humor as the shadowwalkers battle to save their magical rainforest home.Caldera always existed in harmony between the creatures who walk by day and those who walk by night—until an ancient evil awakened. In the year since the shadowwalkers’ narrow escape from the Ant Queen, the ants’ destruction has only spread.Gogi, a shadowwalker monkey still learning to wield his fire powers, embarks on a quest with his friends—including a healing bat, an invisible panther, and a tree frog who controls the winds—for a powerful object that can harness the magic of the eclipse to defeat the Ant Queen.But with just weeks before the next eclipse, Gogi must race to prove that he can control the mighty depths of his talent if he is to protect his friends, save the rainforest, and return home unsinged.

这是一部完全用短信、颜文字、表情符、笔记、邮件写出的小说，幽默易读，走进真实的美国中学生活。 Three BFFs try to make new friends but keep the old in the fifth book in Lisa Greenwald’s hilarious series told entirely in text messages, emojis, and notes. Perfect for fans of Invisible Emmie and the Dork Diaries books.Making new friends is a good thing, right? Not when you barely see your besties! Between swim team, the school play, and poetry club, BFFs Cece, Gabby, and Prianka are meeting different people and trying different things. But besties clash when Gabby’s new friends rank the other girls in their grade in categories like looks, smarts, and popularity.The question is: How can you be your best self if your BFFs don’t have your back?

The bestselling classic set in South Africa during the apartheid era, in which two siblings must face the dangers of their divided country. Mma lives and works in Johannesburg, far from the village thirteen-year-old Naledi and her younger brother, Tiro, call home. When their baby sister suddenly becomes very sick, Naledi and Tiro know that they need to bring their mother back in order to save their sister’s life. Bravely, secretly, they set off on the long journey to the big city to find Mma. It isn’t until they finally reach Jo’burg that they see up close what life is like for black citizens across South Africa—and begin to really question the unfair and dangerous laws of apartheid.

Ace and Ridge are back to save their friend—and the world—in this sequel to The Wishmakers, which Chris Grabenstein, #1 New York Times bestselling author of Escape from Mr. Lemoncello’s Library, praised as a “fantastically fast-paced and funny read.”Being a Wishmaker may be more trouble than it’s worth. Sure, you get a genie who can grant an unlimited number of wishes, but for each one you make you have to accept an awful consequence in return. Not to mention that you’re also given an impossible quest and only seven days to fulfill it!Despite all that, Ace and his genie, Ridge, managed to complete their last mission—but they couldn’t save their friend Tina from being abducted by a rogue genie who’s bent on using his limitless power to rule the world. To rescue her, Ace must reunite with Ridge to become a Wishmaker once more, and they’ll need to team up with the unlikeliest of new allies. It’s not every day you get a second chance to save the world, so Ace is determined to learn from his past mistakes and wish for the best, literally.Perfect for fans of Max Brailler, Adam Gidwitz, and Dan Gutman, this middle grade series is a wonderful mix of unpredictable magic, zany humor, and daring adventure. “An ingenious premise” raved Kirkus in a starred review!

Bayesian modeling with PyMC3 and exploratory analysis of Bayesian models with ArviZ Key Features *A step-by-step guide to conduct Bayesian data analyses using PyMC3 and ArviZ *A modern, practical and computational approach to Bayesian statistical modeling *A tutorial for Bayesian analysis and best practices with the help of sample problems and practice exercises. Book Description The second edition of Bayesian Analysis with Python is an introduction to the main concepts of applied Bayesian inference and its practical implementation in Python using PyMC3, a state-of-the-art probabilistic programming library, and ArviZ, a new library for exploratory analysis of Bayesian models. The main concepts of Bayesian statistics are covered using a practical and computational approach. Synthetic and real data sets are used to introduce several types of models, such as generalized linear models for regression and classification, mixture models, hierarchical models, and Gaussian processes, among others. By the end of the book, you will have a working knowledge of probabilistic modeling and you will be able to design and implement Bayesian models for your own data science problems. After reading the book you will be better prepared to delve into more advanced material or specialized statistical modeling if you need to. What you will learn *Build probabilistic models using the Python library PyMC3 *Analyze probabilistic models with the help of ArviZ *Acquire the skills required to sanity check models and modify them if necessary *Understand the advantages and caveats of hierarchical models *Find out how different models can be used to answer different data analysis questions *Compare models and choose between alternative ones *Discover how different models are unified from a probabilistic perspective *Think probabilistically and benefit from the flexibility of the Bayesian framework Who this book is for If you are a student, data scientist, researcher, or a developer looking to get started with Bayesian data analysis and probabilistic programming, this book is for you. The book is introductory so no previous statistical knowledge is required, although some experience in using Python and NumPy is expected.

Leverage PowerShell to perform many day-to-day tasks in Microsoft Azure Key Features *Deploy and manage Azure virtual machines with PowerShell commands. *Get to grips with core concept of Azure PowerShell such as working with images and disks, custom script extension, high availability and more. *Leverage hands-on projects to successfully apply what you learned through the course of this book. Book Description As an IT professional, it is important to keep up with cloud technologies and learn to manage those technologies. PowerShell is a critical tool that must be learned in order to effectively and more easily manage many Azure resources. This book is designed to teach you to leverage PowerShell to enable you to perform many day-to-day tasks in Microsoft Azure. Taking you through the basic tasks of installing Azure PowerShell and connecting to Azure, you will learn to properly connect to an Azure tenant with PowerShell. Next, you will dive into tasks such as deploying virtual machines with PowerShell, resizing them, and managing their power states with PowerShell. Then, you will learn how to complete more complex Azure tasks with PowerShell, such as deploying virtual machines from custom images, creating images from existing virtual machines, and creating and managing of data disks. Later, you will learn how to snapshot virtual machines, how to encrypt virtual machines, and how to leverage load balancers to ensure high availability with PowerShell. By the end of this book, you will have developed dozens of PowerShell skills that are invaluable in the deployment and management of Azure virtual machines. What you will learn *Manage virtual machines with PowerShell *Resize a virtual machine with PowerShell *Create OS disk snapshots via PowerShell *Deploy new virtual machines from snapshots via PowerShell *Provision and attach data disks to a virtual machine via PowerShell *Load balance virtual machines with PowerShell *Manage virtual machines with custom script extensions Who this book is for This book is intended for IT professionals who are responsible for managing Azure virtual machines. No prior PowerShell or Azure experience is needed.

Learn development skills and improve productivity when programming in Microsoft Dynamics NAV 2018 - the popular Enterprise Resourse Planning management system used across a variety of industries for business process management Key Features *Solve common business problems with the valuable features and flexibility of Dynamics NAV *Understand the structure of NAV database - how documents and business entities are mapped to DB tables *Design user interface and bind the presentation layer with the data storage Book Description Microsoft Dynamics NAV is an enterprise resource planning (ERP) software suite for organizations. The system offers specialized functionality for manufacturing, distribution, government, retail, and other industries. This book gets you started with its integrated development environment for solving problems by customizing business processes. This book introduces the NAV development environment – C/SIDE. It gives an overview of the internal system language and the most essential development tools. The book will enable the reader to customize and extend NAV functionality with C/AL code, design a user interface through pages, create role centers, and build advanced reports in Microsoft Visual Studio. By the end of the book, you will have learned how to extend the NAV data model, how to write and debug custom code, and how to exchange data with external applications. What you will learn *Manage NAV Server configuration with Microsoft Management Console *Manage NAV installation with the NAV Administration Shell *Create integration events and extend functionality via the NAV event model *Run XML Ports from C/AL code *Design reports and write client code in RDLC expressions Who this book is for This book is for experienced NAV users who have an understanding of basic programming concepts. Familiarity with NAV development environment or its internal development language-C/AL is not expected.

Architect scalable, reliable, and maintainable applications for enterprises with Python Key Features *Explore various Python design patterns used for enterprise software development *Apply best practices for testing and performance optimization to build stable applications *Learn about different attacking strategies used on enterprise applications and how to avoid them Book Description Dynamically typed languages like Python are continuously improving. With the addition of exciting new features and a wide selection of modern libraries and frameworks, Python has emerged as an ideal language for developing enterprise applications. Hands-On Enterprise Application Development with Python will show you how to build effective applications that are stable, secure, and easily scalable. The book is a detailed guide to building an end-to-end enterprise-grade application in Python. You will learn how to effectively implement Python features and design patterns that will positively impact your application lifecycle. The book also covers advanced concurrency techniques that will help you build a RESTful application with an optimized frontend. Given that security and stability are the foundation for an enterprise application, you’ll be trained on effective testing, performance analysis, and security practices, and understand how to embed them in your codebase during the initial phase. You’ll also be guided in how to move on from a monolithic architecture to one that is service oriented, leveraging microservices and serverless deployment techniques. By the end of the book, you will have become proficient at building efficient enterprise applications in Python. What you will learn *Understand the purpose of design patterns and their impact on application lifecycle *Build applications that can handle large amounts of data-intensive operations *Uncover advanced concurrency techniques and discover how to handle a large number of requests in production *Optimize frontends to improve the client-side experience of your application *Effective testing and performance profiling techniques to detect issues in applications early in the development cycle *Build applications with a focus on security *Implement large applications as microservices to improve scalability Who this book is for If you’re a developer who wants to build enterprise-grade applications, this book is for you. Basic to intermediate-level of programming experience with Python and database systems is required to understand the concepts covered in this book.

【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。

【本书内容与特】 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。

【本书内容与特】 一、试题解析。重介绍了出题形式和解题技巧以及解题时的逐一实现,使学习者有效把握考查的范围和解题时的阅读重。二、题型分析。按出题题型详细讲解了每个题型的出题形式和解题要求,并根据掌握的知识练习每个题型中配备的练习题。三、综合练习。主要设置了中篇文章阅读练习,是第二部分“题型分析”的集大成。解题技巧和方法可以参考“题型分析”中介绍的知识。四、实战演练。配备两套模拟测验题,题型完全对应真题,难易度近真题,有助于学习者有效检验和评价自己的学习效果。

一、正文。正文按场景分类，每个大类中又分若干小项，如“生计?工作”中包含“生计”“产业”“职场”等小项，这样能让学习者在把握出题范围的同时，了解各个类别中的近义词表达。正文中的例句简短、精练。通过对例句的学习，学习者可以掌握单词*核心的用法。全书所有例句均标注注音假名，以便学习者学习。二、课后练习。练习不仅采用了出题形式中的题型，还根据学习需要，增加了“汉字书写”“读音书写”“词语搭配”等题型，从而帮助学习者更全面地掌握词语的应用知识。三、模拟试题。选择出题频率高的词汇作为考查对象，有助于学习者有效检验和评价自己的学习效果和实战能力。

一、正文。由“语法与解说”“归纳与应用”两部分构成。“语法与解说”部分，按语法的功能行分类梳理，这样不仅可以使学习者有效地掌握各语法功能中的语法条目，还可以学习相近语法条目的意义和用法。“归纳与应用”部分，根据考题中的题型2 和题型3 的要求，重对出现频率高的考查项目行归纳与整理，以便学习者全面了解和掌握知识。譬如“敬语表达”“副词”“续词”“指示词”以及“时态”等考内容。二、课后练习。采用了三项选择题的形式，既包含语句结构方面的知识，也有句法、推论等方面的知识，学习者不仅可以通过练习巩固每课学习内容，还可以熟悉出题方式，在正式考试中应对自如。三、模拟试题。精选出题频率高的语法条目和语法知识作为考查对象，有助于学习者有效检验和评价自己的学习效果和实战能力。

一、正文。正文按场景分类，每个大类中又分若干小项，如“事物的动向”中包含“存在”“移动”“触”等小项，这样能让学习者在把握出题范围的同时，了解各个类别中的近义词表达。正文中的例句简短、精练。通过对例句的学习，学习者可以掌握单词*核心的用法。全书所有例句均标注注音假名，以便学习者学习。二、课后练习。练习不仅采用了出题形式中的题型，还根据学习需要，增加了“汉字书写”“读音书写”“词语搭配”等题型，从而帮助学习者更全面地掌握词语的应用知识。三、模拟试题。选择出题频率高的词汇作为考查对象，有助于学习者有效检验和评价自己的学习效果和实战能力。

《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。