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総義歯臨床のHands-on “保険＆自費”どちらにも対応します（開業医のための実践デンチャーシリーズ） [ 松下寛 ] 楽天ブックス	“保険＆自費”どちらにも対応します開業医のための実践デンチャーシリーズ松下寛杉山雅規デンタルダイヤモンド社BKSCPN_【高額商品】ソウギシリンショウノハンズオンマツシタ,ヒロシスギヤマ,マサキ発行年月：2013年11月ページ数：171p サイズ：単行本 ISBN：9784885102875 松下寛（マツシタヒロシ） 1982年東北大学歯学部卒業。1986年東北大学大学院歯学専攻科修了（歯学臨床系）。東北大学歯学部歯科保存学第一講座（歯内療法学）入局。1988年城南福祉医療協会大田歯科入職。2002年板橋区にて開業。2005年世田谷区にて分院まつした歯科開業。現在、歯学博士。JDA正会員。BPSクリニカルメンバー。昭和大学歯学部口腔解剖学講座講師（兼任）。日本歯内療法学会専門医杉山雅規（スギヤママサキ） 1988年3月日本大学歯学部付属歯科技工専門学校卒業。1990年9月（株）デンティア入社義歯部配属。2010年3月Ivoclar　Vivadent本社研修センター（リヒテンシュタイン）にてBPS研修終了。BPS認定技工士取得。5月社屋移転および取締役就任。2012年8月VITA本社（ドイツ）にてVITAPANを用いたコンプリートデンチャーのセットアップコース受講（本データはこの書籍が刊行された当時に掲載されていたものです） 1　総義歯作製へのアプローチ（どのように研鑽を積んだら、患者が満足する総義歯ができるか／よい義歯、使える義歯の条件とは／総義歯の段階的上達論ーいきなり最上級をめざすな！）／2　「患者＆術者」を救うテクニック（総義歯の咬合ーどのように診査・調整するか／エラーの少ない咬合採得を行うには？／下顎吸着総義歯の概念に基づいた「標準的」な総義歯の形態／既製トレーによる下顎アルジネート印象採得のコツ／義歯の作製は「保険か、自費か」ーその選択と工程）／3　総義歯臨床自費or保険（自費診療／保険診療）総義歯作りの“手・加減”をマスターすれば保険（のギシ）も自費（のギシ）も自由自在！！本医学・薬学・看護学・歯科学歯科医学歯科保存学・歯科補綴学	7,920円
Hands-On High Performance Programming with Qt 5 Build cross-platform applications using concurrency, parallel programming, and memory management【電子書籍】[ Marek Krajewski ] 楽天Kobo電子書籍ストア	＜p＞＜strong＞Build efficient and fast Qt applications, target performance problems, and discover solutions to refine your code＜/strong＞＜/p＞＜h4＞Key Features＜/h4＞＜ul＞＜li＞Build efficient and concurrent applications in Qt to create cross-platform applications＜/li＞＜li＞Identify performance bottlenecks and apply the correct algorithm to improve application performance＜/li＞＜li＞Delve into parallel programming and memory management to optimize your code＜/li＞＜/ul＞＜h4＞Book Description＜/h4＞＜p＞Achieving efficient code through performance tuning is one of the key challenges faced by many programmers. This book looks at Qt programming from a performance perspective. You'll explore the performance problems encountered when using the Qt framework and means and ways to resolve them and optimize performance.＜/p＞＜p＞The book highlights performance improvements and new features released in Qt 5.9, Qt 5.11, and 5.12 (LTE). You'll master general computer performance best practices and tools, which can help you identify the reasons behind low performance, and the most common performance pitfalls experienced when using the Qt framework. In the following chapters, you'll explore multithreading and asynchronous programming with C++ and Qt and learn the importance and efficient use of data structures. You'll also get the opportunity to work through techniques such as memory management and design guidelines, which are essential to improve application performance. Comprehensive sections that cover all these concepts will prepare you for gaining hands-on experience of some of Qt's most exciting application fields - the mobile and embedded development domains.＜/p＞＜p＞By the end of this book, you'll be ready to build Qt applications that are more efficient, concurrent, and performance-oriented in nature＜/p＞＜h4＞What you will learn＜/h4＞＜ul＞＜li＞Understand classic performance best practices＜/li＞＜li＞Get to grips with modern hardware architecture and its performance impact＜/li＞＜li＞Implement tools and procedures used in performance optimization＜/li＞＜li＞Grasp Qt-specific work techniques for graphical user interface (GUI) and platform programming＜/li＞＜li＞Make Transmission Control Protocol (TCP) and Hypertext Transfer Protocol (HTTP) performant and use the relevant Qt classes＜/li＞＜li＞Discover the improvements Qt 5.9 (and the upcoming versions) holds in store＜/li＞＜li＞Explore Qt's graphic engine architecture, strengths, and weaknesses＜/li＞＜/ul＞＜h4＞Who this book is for＜/h4＞＜p＞This book is designed for Qt developers who wish to build highly performance applications for desktop and embedded devices. Programming Experience with C++ is required.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	3,858円
Hands-On Value-at-Risk and Expected Shortfall A Practical Primer【電子書籍】[ Martin Auer ] 楽天Kobo電子書籍ストア	＜p＞This book describes a maximally simple market risk model that is still practical and main risk measures like the value-at-risk and the expected shortfall. It outlines the model's (i) underlying math, (ii) daily operation, and (iii) implementation, while stripping away statistical overhead to keep the concepts accessible. The author selects and weighs the various model features, motivating the choices under real-world constraints, and addresses the evermore important handling of regulatory requirements. The book targets not only practitioners new to the field but also experienced market risk operators by suggesting useful data analysis procedures and implementation details. It furthermore addresses market risk consumers such as managers, traders, and compliance officers by making the model behavior intuitively transparent.＜/p＞＜p＞＜em＞A very useful guide to the theoretical and practical aspects of implementing and operating a risk-monitoring system for a mid-size financial institution. It sets a common body of knowledge to facilitate communication between risk managers, computer and investment specialists by bridging their diverse backgrounds.＜/em＞＜/p＞＜p＞＜strong＞Giovanni Barone-Adesi＜/strong＞ー Professor, Universit? della Svizzera italiana＜/p＞＜p＞＜em＞This unassuming and insightful book starts from the basics and plainly brings the reader up to speed on both theory and implementation.＜/em＞＜/p＞＜p＞＜strong＞Shane Hegarty＜/strong＞ー Director Trade Floor Risk Management, Scotiabank＜/p＞＜p＞Visit the book’s website at www.value-at-risk.com.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	6,928円
Hands-On Unity 2021 Game Development Create, customize, and optimize your own professional games from scratch with Unity 2021, 2nd Edition【電子書籍】[ Nicolas Alejandro Borromeo ] 楽天Kobo電子書籍ストア	＜p＞＜strong＞Achieve mesmerizing game experiences using the latest Unity 2021 features by following a practical approach to building professional games＜/strong＞＜/p＞＜h4＞Key Features＜/h4＞＜ul＞＜li＞Unleash the capabilities of C# scripting to create UIs, graphics, game AI agents and more＜/li＞＜li＞Explore Unity's latest tools, including Universal Render Pipeline, Shader Graph, UI Toolkit, Visual Scripting, and VFX graph, to enhance graphics and animation＜/li＞＜li＞Build an AR experience using Unity's AR Foundation＜/li＞＜/ul＞＜h4＞Book Description＜/h4＞＜p＞Learning how to use Unity is the quickest way to creating a full game, but that's not all you can do with this simple, yet comprehensive suite of video game development tools ? Unity is just as useful for creating AR/VR experiences, complex simulations, real-time realistic rendering, films, and practical games for training and education.＜/p＞＜p＞Hands-On Unity 2021 Game Development outlines a practical journey to creating your first full game from the ground up, building it step-by-step and applying your knowledge as you progress.＜/p＞＜p＞Complete with hands-on tutorials and projects, this easy-to-follow guide will teach you how to develop the game using several Unity tools. As you advance, you will learn how to use the Unity engine, create simple scripts using C#, integrate graphics, sound, and animations, and manipulate physics to create interesting mechanics for your game. You'll be able to apply all the knowledge that you gain to a real-world game.＜/p＞＜p＞Later chapters will show you how to code a simple AI agent to challenge the user and use profiling tools to ensure that the code runs efficiently. Finally, you'll work with Unity's AR tools to create AR experiences for 3D apps and games.＜/p＞＜p＞By the end of this Unity book, you will have created a complete game and built a solid foundation in using a wide variety of Unity tools.＜/p＞＜h4＞What you will learn＜/h4＞＜ul＞＜li＞Explore both C# and Visual Scripting tools to customize various aspects of a game, such as physics, gameplay, and the UI＜/li＞＜li＞Program rich shaders and effects using Unity's new Shader Graph and Universal Render Pipeline＜/li＞＜li＞Implement postprocessing to improve graphics quality with full-screen effects＜/li＞＜li＞Create rich particle systems for your Unity games from scratch using VFX Graph and Shuriken＜/li＞＜li＞Add animations to your game using the Animator, Cinemachine, and Timeline＜/li＞＜li＞Use the brand new UI Toolkit package to create user interfaces＜/li＞＜li＞Implement game AI to control character behavior＜/li＞＜/ul＞＜h4＞Who this book is for＜/h4＞＜p＞This book is best suited for game developers looking to upgrade their knowledge and those who want to migrate their existing skills to the Unity game engine. Those with prior Unity knowledge will also benefit from the chapters exploring the latest features. While you'll still able to follow along if you don't have any programming experience, knowing the fundamentals of C# programming will help you get the most out of this book.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	3,858円
Practical Threat Intelligence and Data-Driven Threat Hunting A hands-on guide to threat hunting with the ATT&CK? Framework and open source tools【電子書籍】[ Valentina Costa-Gazcon ] 楽天Kobo電子書籍ストア	＜p＞＜strong＞Get to grips with cyber threat intelligence and data-driven threat hunting while exploring expert tips and techniques＜/strong＞＜/p＞＜h4＞Key Features＜/h4＞＜ul＞＜li＞Set up an environment to centralize all data in an Elasticsearch, Logstash, and Kibana (ELK) server that enables threat hunting＜/li＞＜li＞Carry out atomic hunts to start the threat hunting process and understand the environment＜/li＞＜li＞Perform advanced hunting using MITRE ATT&CK Evals emulations and Mordor datasets＜/li＞＜/ul＞＜h4＞Book Description＜/h4＞＜p＞Threat hunting (TH) provides cybersecurity analysts and enterprises with the opportunity to proactively defend themselves by getting ahead of threats before they can cause major damage to their business.＜/p＞＜p＞This book is not only an introduction for those who don't know much about the cyber threat intelligence (CTI) and TH world, but also a guide for those with more advanced knowledge of other cybersecurity fields who are looking to implement a TH program from scratch.＜/p＞＜p＞You will start by exploring what threat intelligence is and how it can be used to detect and prevent cyber threats. As you progress, you'll learn how to collect data, along with understanding it by developing data models. The book will also show you how to set up an environment for TH using open source tools. Later, you will focus on how to plan a hunt with practical examples, before going on to explore the MITRE ATT&CK framework.＜/p＞＜p＞By the end of this book, you'll have the skills you need to be able to carry out effective hunts in your own environment.＜/p＞＜h4＞What you will learn＜/h4＞＜ul＞＜li＞Understand what CTI is, its key concepts, and how it is useful for preventing threats and protecting your organization＜/li＞＜li＞Explore the different stages of the TH process＜/li＞＜li＞Model the data collected and understand how to document the findings＜/li＞＜li＞Simulate threat actor activity in a lab environment＜/li＞＜li＞Use the information collected to detect breaches and validate the results of your queries＜/li＞＜li＞Use documentation and strategies to communicate processes to senior management and the wider business＜/li＞＜/ul＞＜h4＞Who this book is for＜/h4＞＜p＞If you are looking to start out in the cyber intelligence and threat hunting domains and want to know more about how to implement a threat hunting division with open-source tools, then this cyber threat intelligence book is for you.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	4,085円
Hands-On Embedded Programming with Qt Develop high performance applications for embedded systems with C++ and Qt 5【電子書籍】[ John Werner ] 楽天Kobo電子書籍ストア	＜p＞＜strong＞A comprehensive guide that will get you up and running with embedded software development using Qt5＜/strong＞＜/p＞＜h4＞Key Features＜/h4＞＜ul＞＜li＞Learn to create fluid, cross-platform applications for embedded devices＜/li＞＜li＞Achieve optimum performance in your applications with QT Lite project＜/li＞＜li＞Explore the implementation of Qt with IoT using QtMqtt, QtKNX, and QtWebSockets＜/li＞＜/ul＞＜h4＞Book Description＜/h4＞＜p＞Qt is an open-source toolkit suitable for cross-platform and embedded application development. This book uses inductive teaching to help you learn how to create applications for embedded and Internet of Things (IoT) devices with Qt 5.＜/p＞＜p＞You'll start by learning to develop your very first application with Qt. Next, you'll build on the first application by understanding new concepts through hands-on projects and written text. Each project will introduce new features that will help you transform your basic first project into a connected IoT application running on embedded hardware. In addition to practical experience in developing an embedded Qt project, you will also gain valuable insights into best practices for Qt development, along with exploring advanced techniques for testing, debugging, and monitoring the performance of Qt applications. Through the course of the book, the examples and projects are demonstrated in a way so that they can be run both locally and on an embedded platform.＜/p＞＜p＞By the end of this book, you will have the skills you need to use Qt 5 to confidently develop modern embedded applications.＜/p＞＜h4＞What you will learn＜/h4＞＜ul＞＜li＞Understand how to develop Qt applications using Qt Creator under Linux＜/li＞＜li＞Explore various Qt GUI technologies to build resourceful and interactive applications＜/li＞＜li＞Understand Qt's threading model to maintain a responsive UI＜/li＞＜li＞Get to grips with remote target load and debug under Qt Creator＜/li＞＜li＞Become adept at writing IoT code using Qt＜/li＞＜li＞Learn a variety of software best practices to ensure that your code is efficient＜/li＞＜/ul＞＜h4＞Who this book is for＜/h4＞＜p＞This book is for software and hardware professionals with experience in different domains who are seeking new career opportunities in embedded systems and IoT. Working knowledge of the C++ Linux command line will be useful to get the most out of this book.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	3,290円
Infrastructure-as-Code Automation Using Terraform, Packer, Vault, Nomad and Consul Hands-on Deployment, Configuration, and Best Practices【電子書籍】[ Navin Sabharwal ] 楽天Kobo電子書籍ストア	＜p＞Discover the methodologies and best practices for getting started with HashiCorp tools, including Terraform, Vault, and Packer. The book begins with an introduction to the infrastructure-as-code concept while establishing the need for automation and management technologies. You’ll go over hands-on deployment, configuration, and best practices for Terraform, Packer, Vault, Nomad, and Consul. You’ll then delve deeper into developing automation code using Terraform for automating AWS/Azure/GCP public cloud tasks; advanced topics include leveraging Vault for secrets management and Packer for image management.＜/p＞＜p＞Along the way you will also look at Nomad and Consul for managing application orchestration along with network interconnectivity. In each chapter you will cover automated infrastructure and application deployment on the VM/container base ecosystem. The book provides sample code and best-practice guidance for developers and architects to look at infrastructure-as-code adoptionfrom a holistic viewpoint.＜/p＞＜p＞All the code presented in the book is available in the form of scripts, which allow you to try out the examples and extend them in interesting ways.＜/p＞＜p＞＜strong＞What You Will Learn＜/strong＞＜/p＞＜ul＞＜li＞Get an overview of the architecture of Terraform, Vault, Packer, Nomad, and Consul＜/li＞＜li＞Follow hands-on steps for enabling Terraform, Vault, Packer, Nomad, and Consul＜/li＞＜li＞Automate various services on the public cloud, including AWS, Azure, and GCP＜/li＞＜/ul＞＜p＞＜strong＞Who This Book Is For＜/strong＞＜/p＞＜p＞Developers, architects, and administrators who want to learn about infrastructure-as-code automation.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	6,685円
Hands-On Machine Learning with TensorFlow.js A guide to building ML applications integrated with web technology using the TensorFlow.js library【電子書籍】[ Kai Sasaki ] 楽天Kobo電子書籍ストア	＜p＞＜strong＞Get hands-on with the browser-based JavaScript library for training and deploying machine learning models effectively＜/strong＞＜/p＞＜h4＞Key Features＜/h4＞＜ul＞＜li＞Build, train and run machine learning models in the browser using TensorFlow.js＜/li＞＜li＞Create smart web applications from scratch with the help of useful examples＜/li＞＜li＞Use flexible and intuitive APIs from TensorFlow.js to understand how machine learning algorithms function＜/li＞＜/ul＞＜h4＞Book Description＜/h4＞＜p＞TensorFlow.js is a framework that enables you to create performant machine learning (ML) applications that run smoothly in a web browser. With this book, you will learn how to use TensorFlow.js to implement various ML models through an example-based approach.＜/p＞＜p＞Starting with the basics, you'll understand how ML models can be built on the web. Moving on, you will get to grips with the TensorFlow.js ecosystem to develop applications more efficiently. The book will then guide you through implementing ML techniques and algorithms such as regression, clustering, fast Fourier transform (FFT), and dimensionality reduction. You will later cover the Bellman equation to solve Markov decision process (MDP) problems and understand how it is related to reinforcement learning. Finally, you will explore techniques for deploying ML-based web applications and training models with TensorFlow Core. Throughout this ML book, you'll discover useful tips and tricks that will build on your knowledge.＜/p＞＜p＞By the end of this book, you will be equipped with the skills you need to create your own web-based ML applications and fine-tune models to achieve high performance.＜/p＞＜h4＞What you will learn＜/h4＞＜ul＞＜li＞Use the t-SNE algorithm in TensorFlow.js to reduce dimensions in an input dataset＜/li＞＜li＞Deploy tfjs-converter to convert Keras models and load them into TensorFlow.js＜/li＞＜li＞Apply the Bellman equation to solve MDP problems＜/li＞＜li＞Use the k-means algorithm in TensorFlow.js to visualize prediction results＜/li＞＜li＞Create tf.js packages with Parcel, Webpack, and Rollup to deploy web apps＜/li＞＜li＞Implement tf.js backend frameworks to tune and accelerate app performance＜/li＞＜/ul＞＜h4＞Who this book is for＜/h4＞＜p＞This book is for web developers who want to learn how to integrate machine learning techniques with web-based applications from scratch. This book will also appeal to data scientists, machine learning practitioners, and deep learning enthusiasts who are looking to perform accelerated, browser-based machine learning on Web using TensorFlow.js. Working knowledge of JavaScript programming language is all you need to get started.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	3,858円
Hands-On Genetic Algorithms with Python Applying genetic algorithms to solve real-world deep learning and artificial intelligence problems【電子書籍】[ Eyal Wirsansky ] 楽天Kobo電子書籍ストア	＜p＞＜strong＞Explore the ever-growing world of genetic algorithms to solve search, optimization, and AI-related tasks, and improve machine learning models using Python libraries such as DEAP, scikit-learn, and NumPy＜/strong＞＜/p＞＜h4＞Key Features＜/h4＞＜ul＞＜li＞Explore the ins and outs of genetic algorithms with this fast-paced guide＜/li＞＜li＞Implement tasks such as feature selection, search optimization, and cluster analysis using Python＜/li＞＜li＞Solve combinatorial problems, optimize functions, and enhance the performance of artificial intelligence applications＜/li＞＜/ul＞＜h4＞Book Description＜/h4＞＜p＞Genetic algorithms are a family of search, optimization, and learning algorithms inspired by the principles of natural evolution. By imitating the evolutionary process, genetic algorithms can overcome hurdles encountered in traditional search algorithms and provide high-quality solutions for a variety of problems. This book will help you get to grips with a powerful yet simple approach to applying genetic algorithms to a wide range of tasks using Python, covering the latest developments in artificial intelligence.＜/p＞＜p＞After introducing you to genetic algorithms and their principles of operation, you'll understand how they differ from traditional algorithms and what types of problems they can solve. You'll then discover how they can be applied to search and optimization problems, such as planning, scheduling, gaming, and analytics. As you advance, you'll also learn how to use genetic algorithms to improve your machine learning and deep learning models, solve reinforcement learning tasks, and perform image reconstruction. Finally, you'll cover several related technologies that can open up new possibilities for future applications.＜/p＞＜p＞By the end of this book, you'll have hands-on experience of applying genetic algorithms in artificial intelligence as well as in numerous other domains.＜/p＞＜h4＞What you will learn＜/h4＞＜ul＞＜li＞Understand how to use state-of-the-art Python tools to create genetic algorithm-based applications＜/li＞＜li＞Use genetic algorithms to optimize functions and solve planning and scheduling problems＜/li＞＜li＞Enhance the performance of machine learning models and optimize deep learning network architecture＜/li＞＜li＞Apply genetic algorithms to reinforcement learning tasks using OpenAI Gym＜/li＞＜li＞Explore how images can be reconstructed using a set of semi-transparent shapes＜/li＞＜li＞Discover other bio-inspired techniques, such as genetic programming and particle swarm optimization＜/li＞＜/ul＞＜h4＞Who this book is for＜/h4＞＜p＞This book is for software developers, data scientists, and AI enthusiasts who want to use genetic algorithms to carry out intelligent tasks in their applications. Working knowledge of Python and basic knowledge of mathematics and computer science will help you get the most out of this book.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	3,290円
Hands-On Agile Software Development with JIRA Design and manage software projects using the Agile methodology【電子書籍】[ David Harned ] 楽天Kobo電子書籍ストア	＜p＞＜strong＞Plan, track, and release great software＜/strong＞＜/p＞＜h4＞Key Features＜/h4＞＜ul＞＜li＞Learn to create reports and dashboard for effective project management＜/li＞＜li＞Implement your development strategy in JIRA.＜/li＞＜li＞Practices to help you manage the issues in the development team＜/li＞＜/ul＞＜h4＞Book Description＜/h4＞＜p＞As teams scale in size, project management can get very complicated. One of the best tools to deal with this kind of problem is JIRA.＜/p＞＜p＞This book will start by organizing your project requirements and the principles of Agile development to get you started. You will then be introduced to set up a JIRA account and the JIRA ecosystem to help you implement a dashboard for your team's work and issues. You will learn how to manage any issues and bugs that might emerge in the development stage. Going ahead, the book will help you build reports and use them to plan the releases based on the study of the reports. Towards the end, you will come across working with the gathered data and create a dashboard that helps you track the project's development.＜/p＞＜h4＞What you will learn＜/h4＞＜ul＞＜li＞Create your first project (and manage existing projects) in JIRA＜/li＞＜li＞Manage your board view and backlogs in JIRA＜/li＞＜li＞Run a Scrum Sprint project in JIRA＜/li＞＜li＞Create reports (including topic-based reports)＜/li＞＜li＞Forecast using versions＜/li＞＜li＞Search for issues with JIRA Query Language (JQL)＜/li＞＜li＞Execute bulk changes to issues＜/li＞＜li＞Create custom filters, dashboards, and widgets＜/li＞＜li＞Create epics, stories, bugs, and tasks＜/li＞＜/ul＞＜h4＞Who this book is for＜/h4＞＜p＞This book is for administrators who wants to apply the Agile approach to managing the issues, bugs, and releases in their software development projects using JIRA.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	2,723円
Hands-On Graph Analytics with Neo4j Perform graph processing and visualization techniques using connected data across your enterprise【電子書籍】[ Estelle Scifo ] 楽天Kobo電子書籍ストア	＜p＞＜strong＞Discover how to use Neo4j to identify relationships within complex and large graph datasets using graph modeling, graph algorithms, and machine learning＜/strong＞＜/p＞＜h4＞Key Features＜/h4＞＜ul＞＜li＞Get up and running with graph analytics with the help of real-world examples＜/li＞＜li＞Explore various use cases such as fraud detection, graph-based search, and recommendation systems＜/li＞＜li＞Get to grips with the Graph Data Science library with the help of examples, and use Neo4j in the cloud for effective application scaling＜/li＞＜/ul＞＜h4＞Book Description＜/h4＞＜p＞Neo4j is a graph database that includes plugins to run complex graph algorithms.＜/p＞＜p＞The book starts with an introduction to the basics of graph analytics, the Cypher query language, and graph architecture components, and helps you to understand why enterprises have started to adopt graph analytics within their organizations. You'll find out how to implement Neo4j algorithms and techniques and explore various graph analytics methods to reveal complex relationships in your data. You'll be able to implement graph analytics catering to different domains such as fraud detection, graph-based search, recommendation systems, social networking, and data management. You'll also learn how to store data in graph databases and extract valuable insights from it. As you become well-versed with the techniques, you'll discover graph machine learning in order to address simple to complex challenges using Neo4j. You will also understand how to use graph data in a machine learning model in order to make predictions based on your data. Finally, you'll get to grips with structuring a web application for production using Neo4j.＜/p＞＜p＞By the end of this book, you'll not only be able to harness the power of graphs to handle a broad range of problem areas, but you'll also have learned how to use Neo4j efficiently to identify complex relationships in your data.＜/p＞＜h4＞What you will learn＜/h4＞＜ul＞＜li＞Become well-versed with Neo4j graph database building blocks, nodes, and relationships＜/li＞＜li＞Discover how to create, update, and delete nodes and relationships using Cypher querying＜/li＞＜li＞Use graphs to improve web search and recommendations＜/li＞＜li＞Understand graph algorithms such as pathfinding, spatial search, centrality, and community detection＜/li＞＜li＞Find out different steps to integrate graphs in a normal machine learning pipeline＜/li＞＜li＞Formulate a link prediction problem in the context of machine learning＜/li＞＜li＞Implement graph embedding algorithms such as DeepWalk, and use them in Neo4j graphs＜/li＞＜/ul＞＜h4＞Who this book is for＜/h4＞＜p＞This book is for data analysts, business analysts, graph analysts, and database developers looking to store and process graph data to reveal key data insights. This book will also appeal to data scientists who want to build intelligent graph applications catering to different domains. Some experience with Neo4j is required.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	3,858円
Hands-On Functional Programming with TypeScript Explore functional and reactive programming to create robust and testable TypeScript applications【電子書籍】[ Remo H. Jansen ] 楽天Kobo電子書籍ストア	＜p＞＜strong＞Discover the power of functional programming, lazy evaluation, monads, concurrency, and immutability to create succinct and expressive implementations＜/strong＞＜/p＞＜h4＞Key Features＜/h4＞＜ul＞＜li＞Get a solid understanding of how to apply functional programming concepts in TypeScript＜/li＞＜li＞Explore TypeScript runtime features such as event loop, closures, and Prototypes＜/li＞＜li＞Gain deeper knowledge on the pros and cons of TypeScript＜/li＞＜/ul＞＜h4＞Book Description＜/h4＞＜p＞Functional programming is a powerful programming paradigm that can help you to write better code. However, learning functional programming can be complicated, and the existing literature is often too complex for beginners. This book is an approachable introduction to functional programming and reactive programming with TypeScript for readers without previous experience in functional programming with JavaScript, TypeScript , or any other programming language.＜/p＞＜p＞The book will help you understand the pros, cons, and core principles of functional programming in TypeScript. It will explain higher order functions, referential transparency, functional composition, and monads with the help of effective code examples. Using TypeScript as a functional programming language, you'll also be able to brush up on your knowledge of applying functional programming techniques, including currying, laziness, and immutability, to real-world scenarios.＜/p＞＜p＞By the end of this book, you will be confident when it comes to using core functional and reactive programming techniques to help you build effective applications with TypeScript.＜/p＞＜h4＞What you will learn＜/h4＞＜ul＞＜li＞Understand the pros and cons of functional programming＜/li＞＜li＞Delve into the principles, patterns, and best practices of functional and reactive programming＜/li＞＜li＞Use lazy evaluation to improve the performance of applications＜/li＞＜li＞Explore functional optics with Ramda＜/li＞＜li＞Gain insights into category theory functional data structures such as Functors and Monads＜/li＞＜li＞Use functions as values, so that they can be passed as arguments to other functions＜/li＞＜/ul＞＜h4＞Who this book is for＜/h4＞＜p＞This book is designed for readers with no prior experience of functional programming with JavaScript, TypeScript or any other programming language. Some familiarity with TypeScript and web development is a must to grasp the concepts in the book easily.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	2,950円
SORACOM実装ガイド公式ワークブック IoT system development,enhanced hands-on commentary.／ソラコム【1000円以上送料無料】 bookfan 2号店楽天市場店	著者ソラコム(著)出版社日経BP発売日2020年03月ISBN9784296105595ページ数383PキーワードそらこむじつそうがいどSORACOM／じつそう／がソラコムジツソウガイドSORACOM／ジツソウ／ガそらこむソラコム9784296105595内容紹介IoTは「テクノロジーの総合格闘技」ハンズオンでノウハウをためよう DX（デジタルトランスフォーメーション）という言葉が広まり、企業のデジタル化はさらに加速しています。DXを技術視点で見た場合、「IoT」は最も注目される技術の1つですが、ポテンシャルから考えればまだまだ普及しているとは言えません。その理由の1つは、IoTは「テクノロジーの総合格闘技」と言われるほど、多くの技術を使うことです。そのため、デバイス・通信・クラウドの各分野の知識が必要で、さらに、それらの上にアプリケーションを実装する必要もあります。これだけ多く知識・のスキルを持っている技術者は少なく、それが普及の阻害要因になっていました。この本では、典型的なIoTシステム開発をハンズオン解説しています。姉妹本である『公式ガイドブック SORACOMプラットフォーム』に掲載した「ユースケース別リファレンスアーキテクチャー」などの実装方法を、基礎的なことから丁寧に説明しています。例えば、・動態管理簡易トラッキング／高精度位置情報トラッキング・環境情報のセンシング・遠隔監視画像の定期アップロード・デバイスの遠隔操作・リアルタイム在庫通知などのIoTシステムの開発方法を1画面1画面、丁寧に解説しています。SORACOMプラットフォームの利用を前提にしていますが、本書を活用すれば、IoTシステム開発の経験値を確実に高めることができます。初めてSORACOMプラットフォームを触る読者を想定していますので、初心者でも迷わずIoTシステム開発を経験できるでしょう。IoT技術者に必携の1冊です!※本データはこの商品が発売された時点の情報です。目次第1部はじめに（本書の目的と対象読者/本書の使い方ほか）/第2部ハンズオンの準備（ハンズオンに必要なもの/アカウントの作成ほか）/第3部 IoTシステム開発をハンズオン解説（動態管理—簡易トラッキング/動態管理—高精度位置情報トラッキングほか）/第4部 Appendix（SORACOM Access Managementのベストプラクティス/LPWAとIoT向け通信の選び方ほか）	3,740円
Interpretable Machine Learning with Python Build explainable, fair, and robust high-performance models with hands-on, real-world examples【電子書籍】[ Serg Mas?s ] 楽天Kobo電子書籍ストア	＜p＞＜b＞A deep dive into the key aspects and challenges of machine learning interpretability using a comprehensive toolkit, including SHAP, feature importance, and causal inference, to build fairer, safer, and more reliable models. Purchase of the print or Kindle book includes a free eBook in PDF format.＜/b＞＜/p＞＜h2＞Key Features＜/h2＞＜ul＞＜li＞Interpret real-world data, including cardiovascular disease data and the COMPAS recidivism scores＜/li＞＜li＞Build your interpretability toolkit with global, local, model-agnostic, and model-specific methods＜/li＞＜li＞Analyze and extract insights from complex models from CNNs to BERT to time series models＜/li＞＜/ul＞＜h2＞Book Description＜/h2＞Interpretable Machine Learning with Python, Second Edition, brings to light the key concepts of interpreting machine learning models by analyzing real-world data, providing you with a wide range of skills and tools to decipher the results of even the most complex models. Build your interpretability toolkit with several use cases, from flight delay prediction to waste classification to COMPAS risk assessment scores. This book is full of useful techniques, introducing them to the right use case. Learn traditional methods, such as feature importance and partial dependence plots to integrated gradients for NLP interpretations and gradient-based attribution methods, such as saliency maps. In addition to the step-by-step code, you’ll get hands-on with tuning models and training data for interpretability by reducing complexity, mitigating bias, placing guardrails, and enhancing reliability. By the end of the book, you’ll be confident in tackling interpretability challenges with black-box models using tabular, language, image, and time series data.＜h2＞What you will learn＜/h2＞＜ul＞＜li＞Progress from basic to advanced techniques, such as causal inference and quantifying uncertainty＜/li＞＜li＞Build your skillset from analyzing linear and logistic models to complex ones, such as CatBoost, CNNs, and NLP transformers＜/li＞＜li＞Use monotonic and interaction constraints to make fairer and safer models＜/li＞＜li＞Understand how to mitigate the influence of bias in datasets＜/li＞＜li＞Leverage sensitivity analysis factor prioritization and factor fixing for any model＜/li＞＜li＞Discover how to make models more reliable with adversarial robustness＜/li＞＜/ul＞＜h2＞Who this book is for＜/h2＞＜p＞This book is for data scientists, machine learning developers, machine learning engineers, MLOps engineers, and data stewards who have an increasingly critical responsibility to explain how the artificial intelligence systems they develop work, their impact on decision making, and how they identify and manage bias. It’s also a useful resource for self-taught ML enthusiasts and beginners who want to go deeper into the subject matter, though a good grasp of the Python programming language is needed to implement the examples.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	4,304円
Hands-on Intermediate Econometrics Using R Templates for Learning Quantitative Methods and R Software【電子書籍】[ Hrishikesh D Vinod ] 楽天Kobo電子書籍ストア	＜p＞How to learn both applied statistics (econometrics) and free, open-source software R? This book allows students to have a sense of accomplishment by copying and pasting many hands-on templates provided here.＜/p＞＜p＞The textbook is essential for anyone wishing to have a practical understanding of an extensive range of topics in Econometrics. No other text provides software snippets to learn so many new statistical tools with hands-on examples. The explicit knowledge of inputs and outputs of each new method allows the student to know which algorithm is worth studying. The book offers sufficient theoretical and algorithmic details about a vast range of statistical techniques.＜/p＞＜p＞The second edition's preface lists the following topics generally absent in other textbooks. (i) Iteratively reweighted least squares, (ii) Pillar charts to represent 3D data. (iii) Stochastic frontier analysis (SFA) (iv) model selection with Mallows' Cp criterion. (v) Hodrick-Prescott (HP) filter. (vi) Automatic ARIMA models. (vi) Nonlinear Granger-causality using kernel regressions and bootstrap confidence intervals. (vii) new Keynesian Phillips curve (NKPC). (viii) Market-neutral pairs trading using two cointegrated stocks. (ix) Artificial neural network (ANN) for product-specific forecasting. (x) Vector AR and VARMA models. (xi) New tools for diagnosing the endogeneity problem. (xii) The elegant set-up of k-class estimators and identification. (xiii) Probit-logit models and Heckman selection bias correction. (xiv) Receiver operating characteristic (ROC) curves and areas under them. (xv) Confusion matrix. (xvi) Quantile regression (xvii) Elastic net estimator. (xviii) generalized Correlations (xix) maximum entropy bootstrap for time series. (xx) Convergence concepts quantified. (xxi) Generalized partial correlation coefficients (xxii) Panel data and duration (survival) models.＜/p＞＜p＞＜strong＞Contents:＜/strong＞＜/p＞＜ul＞＜li＞Production Function and Regression Methods Using R＜/li＞＜li＞Univariate Time Series Analysis with R＜/li＞＜li＞Bivariate Time Series Analysis Including Stochastic Diffusion and Cointegration＜/li＞＜li＞Utility Theory and Empirical Implications＜/li＞＜li＞Vector Models for Multivariate Problems＜/li＞＜li＞Simultaneous Equation Models＜/li＞＜li＞Limited Dependent Variable (GLM) Models＜/li＞＜li＞Consumption and Demand: Kernel Regressions and Machine Learning＜/li＞＜li＞Single, Double, and Maximum Entropy Bootstrap and Inference＜/li＞＜li＞Generalized Least Squares, VARMA, and Estimating Functions＜/li＞＜li＞Box?Cox, Loess, Projection Pursuit, Quantile and Threshold Regression＜/li＞＜li＞Miscellany: Dependence, Correlations, Information Entropy, Causality, Panel Data, and Exact Stochastic Dominance＜/li＞＜/ul＞＜p＞＜strong＞Readership:＜/strong＞ Undergraduate and graduate students of economics and econometrics, applied statisticians and finance professionals.＜br /＞＜strong＞Key Features:＜/strong＞＜/p＞＜ul＞＜li＞Uniquely comprehensive coverage, including many very recently developed topics＜/li＞＜li＞Includes software snippets (that help learn the R language) for readers who are not interested in economics examples＜/li＞＜/ul＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	7,037円
Hands-On AWS Penetration Testing with Kali Linux Set up a virtual lab and pentest major AWS services, including EC2, S3, Lambda, and CloudFormation【電子書籍】[ Karl Gilbert ] 楽天Kobo電子書籍ストア	＜p＞＜strong＞Identify tools and techniques to secure and perform a penetration test on an AWS infrastructure using Kali Linux＜/strong＞＜/p＞＜h4＞Key Features＜/h4＞＜ul＞＜li＞Efficiently perform penetration testing techniques on your public cloud instances＜/li＞＜li＞Learn not only to cover loopholes but also to automate security monitoring and alerting within your cloud-based deployment pipelines＜/li＞＜li＞A step-by-step guide that will help you leverage the most widely used security platform to secure your AWS Cloud environment＜/li＞＜/ul＞＜h4＞Book Description＜/h4＞＜p＞The cloud is taking over the IT industry. Any organization housing a large amount of data or a large infrastructure has started moving cloud-ward ー and AWS rules the roost when it comes to cloud service providers, with its closest competitor having less than half of its market share. This highlights the importance of security on the cloud, especially on AWS. While a lot has been said (and written) about how cloud environments can be secured, performing external security assessments in the form of pentests on AWS is still seen as a dark art.＜/p＞＜p＞This book aims to help pentesters as well as seasoned system administrators with a hands-on approach to pentesting the various cloud services provided by Amazon through AWS using Kali Linux. To make things easier for novice pentesters, the book focuses on building a practice lab and refining penetration testing with Kali Linux on the cloud. This is helpful not only for beginners but also for pentesters who want to set up a pentesting environment in their private cloud, using Kali Linux to perform a white-box assessment of their own cloud resources. Besides this, there is a lot of in-depth coverage of the large variety of AWS services that are often overlooked during a pentest ー from serverless infrastructure to automated deployment pipelines.＜/p＞＜p＞By the end of this book, you will be able to identify possible vulnerable areas efficiently and secure your AWS cloud environment.＜/p＞＜h4＞What you will learn＜/h4＞＜ul＞＜li＞Familiarize yourself with and pentest the most common external-facing AWS services＜/li＞＜li＞Audit your own infrastructure and identify flaws, weaknesses, and loopholes＜/li＞＜li＞Demonstrate the process of lateral and vertical movement through a partially compromised AWS account＜/li＞＜li＞Maintain stealth and persistence within a compromised AWS account＜/li＞＜li＞Master a hands-on approach to pentesting＜/li＞＜li＞Discover a number of automated tools to ease the process of continuously assessing and improving the security stance of an AWS infrastructure＜/li＞＜/ul＞＜h4＞Who this book is for＜/h4＞＜p＞If you are a security analyst or a penetration tester and are interested in exploiting Cloud environments to reveal vulnerable areas and secure them, then this book is for you.＜/p＞＜p＞A basic understanding of penetration testing, cloud computing, and its security concepts is mandatory.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	3,858円
Hands-On Microservices with Spring Boot and Spring Cloud Build and deploy Java microservices using Spring Cloud, Istio, and Kubernetes【電子書籍】[ Magnus Larsson ] 楽天Kobo電子書籍ストア	＜p＞＜b＞Apply microservices patterns to build resilient and scalable distributed systems＜/b＞＜/p＞＜h2＞Key Features＜/h2＞＜ul＞＜li＞Understand the challenges of building large-scale microservice landscapes＜/li＞＜li＞Build cloud-native production-ready microservices with this comprehensive guide＜/li＞＜li＞Discover how to get the best out of Spring Cloud, Kubernetes, and Istio when used together＜/li＞＜/ul＞＜h2＞Book Description＜/h2＞Microservices architecture allows developers to build and maintain applications with ease, and enterprises are rapidly adopting it to build software using Spring Boot as their default framework. With this book, you’ll learn how to efficiently build and deploy microservices using Spring Boot. This microservices book will take you through tried and tested approaches to building distributed systems and implementing microservices architecture in your organization. Starting with a set of simple cooperating microservices developed using Spring Boot, you’ll learn how you can add functionalities such as persistence, make your microservices reactive, and describe their APIs using Swagger/OpenAPI. As you advance, you’ll understand how to add different services from Spring Cloud to your microservice system. The book also demonstrates how to deploy your microservices using Kubernetes and manage them with Istio for improved security and traffic management. Finally, you’ll explore centralized log management using the EFK stack and monitor microservices using Prometheus and Grafana. By the end of this book, you’ll be able to build microservices that are scalable and robust using Spring Boot and Spring Cloud.＜h2＞What you will learn＜/h2＞＜ul＞＜li＞Build reactive microservices using Spring Boot＜/li＞＜li＞Develop resilient and scalable microservices using Spring Cloud＜/li＞＜li＞Use OAuth 2.0/OIDC and Spring Security to protect public APIs＜/li＞＜li＞Implement Docker to bridge the gap between development, testing, and production＜/li＞＜li＞Deploy and manage microservices using Kubernetes＜/li＞＜li＞Apply Istio for improved security, observability, and traffic management＜/li＞＜/ul＞＜h2＞Who this book is for＜/h2＞＜p＞This book is for Java and Spring developers and architects who want to learn how to break up their existing monoliths into microservices and deploy them either on-premises or in the cloud using Kubernetes as a container orchestrator and Istio as a service Mesh. No familiarity with microservices architecture is required to get started with this book.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	5,166円
Hands-on Qt for Python Developers【電子書籍】[ Volodymyr Kirichinets ] 楽天Kobo電子書籍ストア	＜ol＞＜li＞Python, Qt and C++ with examples.＜/li＞＜li＞QML and Qt Quick with examples.＜/li＞＜li＞PyQt and PySide with examples.＜/li＞＜li＞Graphics, Graphical Effects and multimedia.＜/li＞＜li＞Working with Databases (SQL, NoSQL).＜/li＞＜li＞Signals, slots, and event handlers with examples.＜/li＞＜li＞Threading and Multiprocessing in examples of large scale constructions.＜/li＞＜/ol＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	935円
Python Crash Course, 2nd Edition A Hands-On, Project-Based Introduction to Programming【電子書籍】[ Eric Matthes ] 楽天Kobo電子書籍ストア	＜p＞The best-selling Python book in the world, with over 1 million copies sold!＜/p＞＜p＞A fast-paced, no-nonsense, updated guide to programming in Python.＜/p＞＜p＞If you've been thinking about learning how to code or picking up Python, this internationally bestselling guide to the most popular programming language is your quickest, easiest way to get started and go! Even if you have no experience whatsoever, ＜em＞Python Crash Course, 2nd Edition＜/em＞, will have you writing programs, solving problems, building computer games, and creating data visualizations in no time.＜/p＞＜p＞You’ll begin with basic concepts like variables, lists, classes, and loopsーwith the help of fun skill-strengthening exercises for every topicーthen move on to making interactive programs and best practices for testing your code. Later chapters put your new knowledge into play with three cool projects: a 2D Space Invaders-style arcade game, a set of responsive data visualizations you’ll build with Python's handy libraries (Pygame, Matplotlib, Plotly, Django), and a customized web app you can deploy online.＜/p＞＜p＞Why wait any longer? Start your engine and code!＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	3,414円
Hands-On Domain-Driven Design with .NET Core Tackling complexity in the heart of software by putting DDD principles into practice【電子書籍】[ Alexey Zimarev ] 楽天Kobo電子書籍ストア	＜p＞＜strong＞Solve complex business problems by understanding users better, finding the right problem to solve, and building lean event-driven systems to give your customers what they really want＜/strong＞＜/p＞＜h4＞Key Features＜/h4＞＜ul＞＜li＞Apply DDD principles using modern tools such as EventStorming, Event Sourcing, and CQRS＜/li＞＜li＞Learn how DDD applies directly to various architectural styles such as REST, reactive systems, and microservices＜/li＞＜li＞Empower teams to work flexibly with improved services and decoupled interactions＜/li＞＜/ul＞＜h4＞Book Description＜/h4＞＜p＞Developers across the world are rapidly adopting DDD principles to deliver powerful results when writing software that deals with complex business requirements. This book will guide you in involving business stakeholders when choosing the software you are planning to build for them. By figuring out the temporal nature of behavior-driven domain models, you will be able to build leaner, more agile, and modular systems.＜/p＞＜p＞You'll begin by uncovering domain complexity and learn how to capture the behavioral aspects of the domain language. You will then learn about EventStorming and advance to creating a new project in .NET Core 2.1; you'll also and write some code to transfer your events from sticky notes to C#. The book will show you how to use aggregates to handle commands and produce events. As you progress, you'll get to grips with Bounded Contexts, Context Map, Event Sourcing, and CQRS. After translating domain models into executable C# code, you will create a frontend for your application using Vue.js. In addition to this, you'll learn how to refactor your code and cover event versioning and migration essentials.＜/p＞＜p＞By the end of this DDD book, you will have gained the confidence to implement the DDD approach in your organization and be able to explore new techniques that complement what you've learned from the book.＜/p＞＜h4＞What you will learn＜/h4＞＜ul＞＜li＞Discover and resolve domain complexity together with business stakeholders＜/li＞＜li＞Avoid common pitfalls when creating the domain model＜/li＞＜li＞Study the concept of Bounded Context and aggregate＜/li＞＜li＞Design and build temporal models based on behavior and not only data＜/li＞＜li＞Explore benefits and drawbacks of Event Sourcing＜/li＞＜li＞Get acquainted with CQRS and to-the-point read models with projections＜/li＞＜li＞Practice building one-way flow UI with Vue.js＜/li＞＜li＞Understand how a task-based UI conforms to DDD principles＜/li＞＜/ul＞＜h4＞Who this book is for＜/h4＞＜p＞This book is for .NET developers who have an intermediate level understanding of C#, and for those who seek to deliver value, not just write code. Intermediate level of competence in JavaScript will be helpful to follow the UI chapters.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	4,085円
Hands-On Julia Programming: An Authoritative Guide to the Production-Ready Systems in Julia (English Edition)【電子書籍】[ Sambit Kumar Dash ] 楽天Kobo電子書籍ストア	＜p＞Build production-ready machine learning and NLP systems using functional programming, development platforms, and cloud deployment.＜/p＞＜p＞KEY FEATURES＜/p＞＜p＞● In-depth explanation and code samples highlighting the features of the Julia language.＜/p＞＜p＞● Extensive coverage of the Julia development ecosystem, package management, DevOps environment integration, and performance management tools.＜/p＞＜p＞● Exposure to the most important Julia packages that aid in Data and Text Analytics and Deep Learning.＜/p＞＜p＞DESCRIPTION＜/p＞＜p＞The Julia Programming language enables data scientists and programmers to create prototypes without sacrificing performance. Nonetheless, skeptics question its readiness for production deployments as a new platform with a 1.0 release in 2018. This book removes these doubts and offers a comprehensive glimpse at the language's use throughout developing and deploying production-ready applications.＜/p＞＜p＞The first part of the book teaches experienced programmers and scientists about the Julia language features in great detail. The second part consists of gaining hands-on experience with the development environment, debugging, programming guidelines, package management, and cloud deployment strategies. In the final section, readers are introduced to a variety of third-party packages available in the Julia ecosystem for Data Processing, Text Analytics, and developing Deep Learning models.＜/p＞＜p＞This book provides an extensive overview of the programming language and broadens understanding of the Julia ecosystem. As a result, it assists programmers, scientists, and information architects in selecting Julia for their next production deployments.＜/p＞＜p＞WHAT YOU WILL LEARN＜/p＞＜p＞● Get to know the complete fundamentals of Julia programming.＜/p＞＜p＞● Explore Julia development frameworks and how to work with them.＜/p＞＜p＞● Dig deeper into the concepts and applications of functional programming.＜/p＞＜p＞● Uncover the Julia infrastructure for development, testing, and deployment.＜/p＞＜p＞● Learn to practice Julia libraries and the Julia package ecosystem.＜/p＞＜p＞● Processing Data, Deep Learning, and Natural Language Processing with Julia.＜/p＞＜p＞WHO THIS BOOK IS FOR＜/p＞＜p＞This book is for Data Scientists and application developers who want to learn about Julia application development. No prior Julia knowledge is required but knowing the basics of programming helps understand the objectives of this book.＜/p＞＜p＞AUTHOR BIO＜/p＞＜p＞Sambit Kumar Dash is an accomplished business manager who focuses on bringing technology product ideas to reality. He has over 20 years of experience in product and business management, architecture, and research and development. He has conceived and developed a PDF reader library in the Julia language.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	2,300円
Hands-On Generative Adversarial Networks with PyTorch 1.x Implement next-generation neural networks to build powerful GAN models using Python【電子書籍】[ John Hany ] 楽天Kobo電子書籍ストア	＜p＞＜strong＞Apply deep learning techniques and neural network methodologies to build, train, and optimize generative network models＜/strong＞＜/p＞＜h4＞Key Features＜/h4＞＜ul＞＜li＞Implement GAN architectures to generate images, text, audio, 3D models, and more＜/li＞＜li＞Understand how GANs work and become an active contributor in the open source community＜/li＞＜li＞Learn how to generate photo-realistic images based on text descriptions＜/li＞＜/ul＞＜h4＞Book Description＜/h4＞＜p＞With continuously evolving research and development, Generative Adversarial Networks (GANs) are the next big thing in the field of deep learning. This book highlights the key improvements in GANs over generative models and guides in making the best out of GANs with the help of hands-on examples.＜/p＞＜p＞This book starts by taking you through the core concepts necessary to understand how each component of a GAN model works. You'll build your first GAN model to understand how generator and discriminator networks function. As you advance, you'll delve into a range of examples and datasets to build a variety of GAN networks using PyTorch functionalities and services, and become well-versed with architectures, training strategies, and evaluation methods for image generation, translation, and restoration. You'll even learn how to apply GAN models to solve problems in areas such as computer vision, multimedia, 3D models, and natural language processing (NLP). The book covers how to overcome the challenges faced while building generative models from scratch. Finally, you'll also discover how to train your GAN models to generate adversarial examples to attack other CNN and GAN models.＜/p＞＜p＞By the end of this book, you will have learned how to build, train, and optimize next-generation GAN models and use them to solve a variety of real-world problems.＜/p＞＜h4＞What you will learn＜/h4＞＜ul＞＜li＞Implement PyTorch's latest features to ensure efficient model designing＜/li＞＜li＞Get to grips with the working mechanisms of GAN models＜/li＞＜li＞Perform style transfer between unpaired image collections with CycleGAN＜/li＞＜li＞Build and train 3D-GANs to generate a point cloud of 3D objects＜/li＞＜li＞Create a range of GAN models to perform various image synthesis operations＜/li＞＜li＞Use SEGAN to suppress noise and improve the quality of speech audio＜/li＞＜/ul＞＜h4＞Who this book is for＜/h4＞＜p＞This GAN book is for machine learning practitioners and deep learning researchers looking to get hands-on guidance in implementing GAN models using PyTorch. You'll become familiar with state-of-the-art GAN architectures with the help of real-world examples. Working knowledge of Python programming language is necessary to grasp the concepts covered in this book.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	3,290円
Learn Physics with Functional Programming A Hands-on Guide to Exploring Physics with Haskell【電子書籍】[ Scott N. Walck ] 楽天Kobo電子書籍ストア	＜p＞＜strong＞Deepen your understanding of physics by learning to use the Haskell functional programming language.＜/strong＞＜/p＞＜p＞＜em＞Learn Physics with Functional Programming＜/em＞ is your key to unlocking the mysteries of theoretical physics by coding the underlying math in Haskell.＜/p＞＜p＞You’ll use Haskell’s type system to check that your code makes sense as you deepen your understanding of Newtonian mechanics and electromagnetic theory, including how to describe and calculate electric and magnetic fields.＜/p＞＜p＞As you work your way through the book’s numerous examples and exercises, you’ll learn how to:＜/p＞＜ul＞＜li＞Encode vectors, derivatives, integrals, scalar fields, vector fields, and differential equations＜/li＞＜li＞Express fundamental physical principles using the logic of Haskell’s type system to clarify Newton’s second law, Coulomb’s law, the Biot-Savart law, and the Maxwell equations＜/li＞＜li＞Use higher-order functions to express numerical integration and approximation methods, such as the Euler method and the finite-difference time-domain (FDTD) method＜/li＞＜li＞Create graphs, models, and animations of physical scenarios like colliding billiard balls, waves in a guitar string, and a proton in a magnetic field＜/li＞＜/ul＞＜p＞Whether you’re using this book as a core textbook for a computational physics course or for self-study, ＜em＞Learn Physics with Functional Programming＜/em＞ will teach you how to use the power of functional programming to explore the beautiful ideas of theoretical physics.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	4,272円
Hands-On Smart Contract Development with Hyperledger Fabric V2【電子書籍】[ Matt Zand ] 楽天Kobo電子書籍ストア	＜p＞Blockchain technology continues to disrupt a wide variety of organizations, from small businesses to the Fortune 500. Today hundreds of blockchain networks are in production, including many built with Hyperledger Fabric. This practical guide shows developers how the latest version of this blockchain infrastructure provides an ideal foundation for developing enterprise blockchain applications or solutions.＜/p＞＜p＞Authors Matt Zand, Xun Wu, and Mark Anthony Morris demonstrate how the versatile design of Hyperledger Fabric 2.0 satisfies a broad range of industry use cases. Developers with or without previous Hyperledger experience will discover why no other distributed ledger technology framework enjoys such wide adoption by cloud service providers such as Amazon, Alibaba, IBM, Google, and Oracle.＜/p＞＜ul＞＜li＞Walk through the architecture and components of Hyperledger Fabric 2.0＜/li＞＜li＞Migrate your current Hyperledger Fabric projects to version 2.0＜/li＞＜li＞Develop blockchain applications on the Hyperledger platform with Node.js＜/li＞＜li＞Deploy and integrate Hyperledger on Amazon Managed Blockchain, IBM Cloud, and Oracle Cloud＜/li＞＜li＞Develop blockchain applications with Hyperledger Aries, Avalon, Besu, and Grid＜/li＞＜li＞Build end-to-end blockchain supply chain applications with Hyperledger＜/li＞＜/ul＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	5,430円
Hands-On Data Science for Marketing Improve your marketing strategies with machine learning using Python and R【電子書籍】[ Yoon Hyup Hwang ] 楽天Kobo電子書籍ストア	＜p＞＜strong＞Optimize your marketing strategies through analytics and machine learning＜/strong＞＜/p＞＜h4＞Key Features＜/h4＞＜ul＞＜li＞Understand how data science drives successful marketing campaigns＜/li＞＜li＞Use machine learning for better customer engagement, retention, and product recommendations＜/li＞＜li＞Extract insights from your data to optimize marketing strategies and increase profitability＜/li＞＜/ul＞＜h4＞Book Description＜/h4＞＜p＞Regardless of company size, the adoption of data science and machine learning for marketing has been rising in the industry. With this book, you will learn to implement data science techniques to understand the drivers behind the successes and failures of marketing campaigns. This book is a comprehensive guide to help you understand and predict customer behaviors and create more effectively targeted and personalized marketing strategies.＜/p＞＜p＞This is a practical guide to performing simple-to-advanced tasks, to extract hidden insights from the data and use them to make smart business decisions. You will understand what drives sales and increases customer engagements for your products. You will learn to implement machine learning to forecast which customers are more likely to engage with the products and have high lifetime value. This book will also show you how to use machine learning techniques to understand different customer segments and recommend the right products for each customer. Apart from learning to gain insights into consumer behavior using exploratory analysis, you will also learn the concept of A/B testing and implement it using Python and R.＜/p＞＜p＞By the end of this book, you will be experienced enough with various data science and machine learning techniques to run and manage successful marketing campaigns for your business.＜/p＞＜h4＞What you will learn＜/h4＞＜ul＞＜li＞Learn how to compute and visualize marketing KPIs in Python and R＜/li＞＜li＞Master what drives successful marketing campaigns with data science＜/li＞＜li＞Use machine learning to predict customer engagement and lifetime value＜/li＞＜li＞Make product recommendations that customers are most likely to buy＜/li＞＜li＞Learn how to use A/B testing for better marketing decision making＜/li＞＜li＞Implement machine learning to understand different customer segments＜/li＞＜/ul＞＜h4＞Who this book is for＜/h4＞＜p＞If you are a marketing professional, data scientist, engineer, or a student keen to learn how to apply data science to marketing, this book is what you need! It will be beneficial to have some basic knowledge of either Python or R to work through the examples. This book will also be beneficial for beginners as it covers basic-to-advanced data science concepts and applications in marketing with real-life examples.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	3,858円
Hands-On Edge Analytics with Azure IoT Design and develop IoT applications with edge analytical solutions including Azure IoT Edge【電子書籍】[ Colin Dow ] 楽天Kobo電子書籍ストア	＜p＞＜strong＞Design, secure, and protect the privacy of edge analytics applications using platforms and tools such as Microsoft's Azure IoT Edge, MicroPython, and Open Source Computer Vision (OpenCV)＜/strong＞＜/p＞＜h4＞Key Features＜/h4＞＜ul＞＜li＞Become well-versed with best practices for implementing automated analytical computations＜/li＞＜li＞Discover real-world examples to extend cloud intelligence＜/li＞＜li＞Develop your skills by understanding edge analytics and applying it to research activities＜/li＞＜/ul＞＜h4＞Book Description＜/h4＞＜p＞Edge analytics has gained attention as the IoT model for connected devices rises in popularity. This guide will give you insights into edge analytics as a data analysis model, and help you understand why it's gaining momentum.＜/p＞＜p＞You'll begin with the key concepts and components used in an edge analytics app. Moving ahead, you'll delve into communication protocols to understand how sensors send their data to computers or microcontrollers. Next, the book will demonstrate how to design modern edge analytics apps that take advantage of the processing power of modern single-board computers and microcontrollers. Later, you'll explore Microsoft Azure IoT Edge, MicroPython, and the OpenCV visual recognition library. As you progress, you'll cover techniques for processing AI functionalities from the server side to the sensory side of IoT. You'll even get hands-on with designing a smart doorbell system using the technologies you've learned. To remove vulnerabilities in the overall edge analytics architecture, you'll discover ways to overcome security and privacy challenges. Finally, you'll use tools to audit and perform real-time monitoring of incoming data and generate alerts for the infrastructure.＜/p＞＜p＞By the end of this book, you'll have learned how to use edge analytics programming techniques and be able to implement automated analytical computations.＜/p＞＜h4＞What you will learn＜/h4＞＜ul＞＜li＞Discover the key concepts and architectures used with edge analytics＜/li＞＜li＞Understand how to use long-distance communication protocols for edge analytics＜/li＞＜li＞Deploy Microsoft Azure IoT Edge to a Raspberry Pi＜/li＞＜li＞Create Node-RED dashboards with MQTT and Text to Speech (TTS)＜/li＞＜li＞Use MicroPython for developing edge analytics apps＜/li＞＜li＞Explore various machine learning techniques and discover how machine learning is related to edge analytics＜/li＞＜li＞Use camera and vision recognition algorithms on the sensory side to design an edge analytics app＜/li＞＜li＞Monitor and audit edge analytics apps＜/li＞＜/ul＞＜h4＞Who this book is for＜/h4＞＜p＞If you are a data analyst, data architect, or data scientist who is interested in learning and practicing advanced automated analytical computations, then this book is for you. You will also find this book useful if you're looking to learn edge analytics from scratch. Basic knowledge of data analytics concepts is assumed to get the most out of this book.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	3,290円
Writing Picture Books Revised and Expanded Edition A Hands-On Guide From Story Creation to Publication【電子書籍】[ Ann Whitford Paul ] 楽天Kobo電子書籍ストア	＜p＞＜strong＞Master the Art of Writing Enthralling Tales for the Youngest pre-and emerging readers!＜/strong＞＜/p＞＜p＞Fully updated and thoroughly revised, ＜em＞Writing Picture Books Revised and Expanded Edition＜/em＞ is the go-to resource for writers crafting stories for children ages two to eight. You'll learn the unique set of skills it takes to bring your story to life by using tightly focused text and leaving room for the illustrator to be creative.＜/p＞＜p＞Award-winning author Ann Whitford Paul helps you develop the skills you need by walking you through techniques and exercises specifically for picture book writers. You'll find:＜/p＞＜p＞? Instruction on generating ideas, creating characters, point-of-view, beginnings and endings, plotting, word count, rhyme, and more＜br /＞ ? Unique methods for using poetic techniques to enrich your writing＜br /＞ ? Hands-on revision exercises (get out your scissors, tape, and highlighters) to help identify problems and improve your picture book manuscripts＜br /＞ ? Updated tips for researching the changing picture book market, approaching publishers, working with an agent, and developing a platform＜br /＞ ? All new quizzes and examples from picture books throughout＜br /＞ ? New chapters cover issues such as page turns, agents, and self-publishing＜/p＞＜p＞Whether you're just starting out as a picture book writer or have tried unsuccessfully to get your work published, ＜em＞Writing Picture Books Revised and Expanded Edition＜/em＞ is just what you need to craft picture books that will appeal to young children and parents, and agents and editors.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	1,747円
Hands-On Machine Learning with C++ Build, train, and deploy end-to-end machine learning and deep learning pipelines【電子書籍】[ Kirill Kolodiazhnyi ] 楽天Kobo電子書籍ストア	＜p＞＜strong＞Implement supervised and unsupervised machine learning algorithms using C++ libraries such as PyTorch C++ API, Caffe2, Shogun, Shark-ML, mlpack, and dlib with the help of real-world examples and datasets＜/strong＞＜/p＞＜h4＞Key Features＜/h4＞＜ul＞＜li＞Become familiar with data processing, performance measuring, and model selection using various C++ libraries＜/li＞＜li＞Implement practical machine learning and deep learning techniques to build smart models＜/li＞＜li＞Deploy machine learning models to work on mobile and embedded devices＜/li＞＜/ul＞＜h4＞Book Description＜/h4＞＜p＞C++ can make your machine learning models run faster and more efficiently. This handy guide will help you learn the fundamentals of machine learning (ML), showing you how to use C++ libraries to get the most out of your data. This book makes machine learning with C++ for beginners easy with its example-based approach, demonstrating how to implement supervised and unsupervised ML algorithms through real-world examples.＜/p＞＜p＞This book will get you hands-on with tuning and optimizing a model for different use cases, assisting you with model selection and the measurement of performance. You'll cover techniques such as product recommendations, ensemble learning, and anomaly detection using modern C++ libraries such as PyTorch C++ API, Caffe2, Shogun, Shark-ML, mlpack, and dlib. Next, you'll explore neural networks and deep learning using examples such as image classification and sentiment analysis, which will help you solve various problems. Later, you'll learn how to handle production and deployment challenges on mobile and cloud platforms, before discovering how to export and import models using the ONNX format.＜/p＞＜p＞By the end of this C++ book, you will have real-world machine learning and C++ knowledge, as well as the skills to use C++ to build powerful ML systems.＜/p＞＜h4＞What you will learn＜/h4＞＜ul＞＜li＞Explore how to load and preprocess various data types to suitable C++ data structures＜/li＞＜li＞Employ key machine learning algorithms with various C++ libraries＜/li＞＜li＞Understand the grid-search approach to find the best parameters for a machine learning model＜/li＞＜li＞Implement an algorithm for filtering anomalies in user data using Gaussian distribution＜/li＞＜li＞Improve collaborative filtering to deal with dynamic user preferences＜/li＞＜li＞Use C++ libraries and APIs to manage model structures and parameters＜/li＞＜li＞Implement a C++ program to solve image classification tasks with LeNet architecture＜/li＞＜/ul＞＜h4＞Who this book is for＜/h4＞＜p＞You will find this C++ machine learning book useful if you want to get started with machine learning algorithms and techniques using the popular C++ language. As well as being a useful first course in machine learning with C++, this book will also appeal to data analysts, data scientists, and machine learning developers who are looking to implement different machine learning models in production using varied datasets and examples. Working knowledge of the C++ programming language is mandatory to get started with this book.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	4,198円
The TensorFlow Workshop A hands-on guide to building deep learning models from scratch using real-world datasets【電子書籍】[ Anthony Maddalone ] 楽天Kobo電子書籍ストア	＜p＞＜strong＞Get started with TensorFlow fundamentals to build and train deep learning models with real-world data, practical exercises, and challenging activities＜/strong＞＜/p＞＜h4＞Key Features＜/h4＞＜ul＞＜li＞Understand the fundamentals of tensors, neural networks, and deep learning＜/li＞＜li＞Discover how to implement and fine-tune deep learning models for real-world datasets＜/li＞＜li＞Build your experience and confidence with hands-on exercises and activities＜/li＞＜/ul＞＜h4＞Book Description＜/h4＞＜p＞Getting to grips with tensors, deep learning, and neural networks can be intimidating and confusing for anyone, no matter their experience level. The breadth of information out there, often written at a very high level and aimed at advanced practitioners, can make getting started even more challenging.＜/p＞＜p＞If this sounds familiar to you, The TensorFlow Workshop is here to help. Combining clear explanations, realistic examples, and plenty of hands-on practice, it'll quickly get you up and running.＜/p＞＜p＞You'll start off with the basics ? learning how to load data into TensorFlow, perform tensor operations, and utilize common optimizers and activation functions. As you progress, you'll experiment with different TensorFlow development tools, including TensorBoard, TensorFlow Hub, and Google Colab, before moving on to solve regression and classification problems with sequential models.＜/p＞＜p＞Building on this solid foundation, you'll learn how to tune models and work with different types of neural network, getting hands-on with real-world deep learning applications such as text encoding, temperature forecasting, image augmentation, and audio processing.＜/p＞＜p＞By the end of this deep learning book, you'll have the skills, knowledge, and confidence to tackle your own ambitious deep learning projects with TensorFlow.＜/p＞＜h4＞What you will learn＜/h4＞＜ul＞＜li＞Get to grips with TensorFlow's mathematical operations＜/li＞＜li＞Pre-process a wide variety of tabular, sequential, and image data＜/li＞＜li＞Understand the purpose and usage of different deep learning layers＜/li＞＜li＞Perform hyperparameter-tuning to prevent overfitting of training data＜/li＞＜li＞Use pre-trained models to speed up the development of learning models＜/li＞＜li＞Generate new data based on existing patterns using generative models＜/li＞＜/ul＞＜h4＞Who this book is for＜/h4＞＜p＞This TensorFlow book is for anyone who wants to develop their understanding of deep learning and get started building neural networks with TensorFlow. Basic knowledge of Python programming and its libraries, as well as a general understanding of the fundamentals of data science and machine learning, will help you grasp the topics covered in this book more easily.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	3,858円
Hands-On Unsupervised Learning with Python Implement machine learning and deep learning models using Scikit-Learn, TensorFlow, and more【電子書籍】[ Giuseppe Bonaccorso ] 楽天Kobo電子書籍ストア	＜p＞＜strong＞Discover the skill-sets required to implement various approaches to Machine Learning with Python＜/strong＞＜/p＞＜h4＞Key Features＜/h4＞＜ul＞＜li＞Explore unsupervised learning with clustering, autoencoders, restricted Boltzmann machines, and more＜/li＞＜li＞Build your own neural network models using modern Python libraries＜/li＞＜li＞Practical examples show you how to implement different machine learning and deep learning techniques＜/li＞＜/ul＞＜h4＞Book Description＜/h4＞＜p＞Unsupervised learning is about making use of raw, untagged data and applying learning algorithms to it to help a machine predict its outcome. With this book, you will explore the concept of unsupervised learning to cluster large sets of data and analyze them repeatedly until the desired outcome is found using Python.＜/p＞＜p＞This book starts with the key differences between supervised, unsupervised, and semi-supervised learning. You will be introduced to the best-used libraries and frameworks from the Python ecosystem and address unsupervised learning in both the machine learning and deep learning domains. You will explore various algorithms, techniques that are used to implement unsupervised learning in real-world use cases. You will learn a variety of unsupervised learning approaches, including randomized optimization, clustering, feature selection and transformation, and information theory. You will get hands-on experience with how neural networks can be employed in unsupervised scenarios. You will also explore the steps involved in building and training a GAN in order to process images.＜/p＞＜p＞By the end of this book, you will have learned the art of unsupervised learning for different real-world challenges.＜/p＞＜h4＞What you will learn＜/h4＞＜ul＞＜li＞Use cluster algorithms to identify and optimize natural groups of data＜/li＞＜li＞Explore advanced non-linear and hierarchical clustering in action＜/li＞＜li＞Soft label assignments for fuzzy c-means and Gaussian mixture models＜/li＞＜li＞Detect anomalies through density estimation＜/li＞＜li＞Perform principal component analysis using neural network models＜/li＞＜li＞Create unsupervised models using GANs＜/li＞＜/ul＞＜h4＞Who this book is for＜/h4＞＜p＞This book is intended for statisticians, data scientists, machine learning developers, and deep learning practitioners who want to build smart applications by implementing key building block unsupervised learning, and master all the new techniques and algorithms offered in machine learning and deep learning using real-world examples. Some prior knowledge of machine learning concepts and statistics is desirable.＜/p＞画面が切り替わりますので、しばらくお待ち下さい。 ※ご購入は、楽天kobo商品ページからお願いします。※切り替わらない場合は、こちらをクリックして下さい。 ※このページからは注文できません。	3,858円