Modern Information Technology and It Education
This book constitutes the refereed proceedings of the 12th International Conference on Modern Information Technology and IT Education, held in Moscow, Russia, in November 2017. The 30 papers presented were carefully reviewed and selected from 126 submissions. The papers are organized according to the following topics: IT-education: methodology, methodological support; e-learning and IT in education; educational resources and best practices of IT-education; research and development in the field of new IT and their applications; scientific software in education and science; school education in computer science and ICT; economic informatics.
Hands-On Data Analysis with Pandas - Second Edition
Get to grips with pandas by working with real datasets and master data discovery, data manipulation, data preparation, and handling data for analytical tasksKey FeaturesPerform efficient data analysis and manipulation tasks using pandas 1.xApply pandas to different real-world domains with the help of step-by-step examplesMake the most of pandas as an effective data exploration toolBook DescriptionExtracting valuable business insights is no longer a 'nice-to-have', but an essential skill for anyone who handles data in their enterprise. Hands-On Data Analysis with Pandas is here to help beginners and those who are migrating their skills into data science get up to speed in no time.This book will show you how to analyze your data, get started with machine learning, and work effectively with the Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn.Using real-world datasets, you will learn how to use the pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will learn how to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding chapters, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data.This updated edition will equip you with the skills you need to use pandas 1.x to efficiently perform various data manipulation tasks, reliably reproduce analyses, and visualize your data for effective decision making - valuable knowledge that can be applied across multiple domains.What you will learnUnderstand how data analysts and scientists gather and analyze dataPerform data analysis and data wrangling using PythonCombine, group, and aggregate data from multiple sourcesCreate data visualizations with pandas, matplotlib, and seabornApply machine learning algorithms to identify patterns and make predictionsUse Python data science libraries to analyze real-world datasetsSolve common data representation and analysis problems using pandasBuild Python scripts, modules, and packages for reusable analysis codeWho this book is forThis book is for data science beginners, data analysts, and Python developers who want to explore each stage of data analysis and scientific computing using a wide range of datasets. Data scientists looking to implement pandas in their machine learning workflow will also find plenty of valuable know-how as they progress.You'll find it easier to follow along with this book if you have a working knowledge of the Python programming language, but a Python crash-course tutorial is provided in the code bundle for anyone who needs a refresher.Table of ContentsIntroduction to Data AnalysisWorking with Pandas DataFramesData Wrangling with PandasAggregating Pandas DataFramesVisualizing Data with Pandas and MatplotlibPlotting with Seaborn and Customization TechniquesFinancial Analysis - Bitcoin and the Stock MarketRule-Based Anomaly DetectionGetting Started with Machine Learning in PythonMaking Better Predictions - Optimizing ModelsMachine Learning Anomaly DetectionThe Road Ahead
Mastering Shiny
Master the Shiny web framework--and take your R skills to a whole new level. By letting you move beyond static reports, Shiny helps you create fully interactive web apps for data analyses. Users will be able to jump between datasets, explore different subsets or facets of the data, run models with parameter values of their choosing, customize visualizations, and much more. Hadley Wickham from RStudio shows data scientists, data analysts, statisticians, and scientific researchers with no knowledge of HTML, CSS, or JavaScript how to create rich web apps from R. This in-depth guide provides a learning path that you can follow with confidence, as you go from a Shiny beginner to an expert developer who can write large, complex apps that are maintainable and performant. Get started: Discover how the major pieces of a Shiny app fit together Put Shiny in action: Explore Shiny functionality with a focus on code samples, example apps, and useful techniques Master reactivity: Go deep into the theory and practice of reactive programming and examine reactive graph components Apply best practices: Examine useful techniques for making your Shiny apps work well in production
Hands-On Financial Trading with Python
Discover how to build and backtest algorithmic trading strategies with ZiplineKey Features: Get to grips with market data and stock analysis and visualize data to gain quality insightsFind out how to systematically approach quantitative research and strategy generation/backtesting in algorithmic tradingLearn how to navigate the different features in Python's data analysis librariesBook Description: Algorithmic trading helps you stay ahead of the markets by devising strategies in quantitative analysis to gain profits and cut losses.The book starts by introducing you to algorithmic trading and explaining why Python is the best platform for developing trading strategies. You'll then cover quantitative analysis using Python, and learn how to build algorithmic trading strategies with Zipline using various market data sources. Using Zipline as the backtesting library allows access to complimentary US historical daily market data until 2018. As you advance, you will gain an in-depth understanding of Python libraries such as NumPy and pandas for analyzing financial datasets, and explore Matplotlib, statsmodels, and scikit-learn libraries for advanced analytics. You'll also focus on time series forecasting, covering pmdarima and Facebook Prophet.By the end of this trading book, you will be able to build predictive trading signals, adopt basic and advanced algorithmic trading strategies, and perform portfolio optimization.What You Will Learn: Discover how quantitative analysis works by covering financial statistics and ARIMAUse core Python libraries to perform quantitative research and strategy development using real datasetsUnderstand how to access financial and economic data in PythonImplement effective data visualization with MatplotlibApply scientific computing and data visualization with popular Python librariesBuild and deploy backtesting algorithmic trading strategiesWho this book is for: This book is for data analysts and financial traders who want to explore how to design algorithmic trading strategies using Python's core libraries. If you are looking for a practical guide to backtesting algorithmic trading strategies and building your own strategies, then this book is for you. Beginner-level working knowledge of Python programming and statistics will be helpful.
Simulation Tools and Techniques
This two-volume set constitutes the refereed post-conference proceedings of the 12th International Conference on Simulation Tools and Techniques, SIMUTools 2020, held in Guiyang, China, in August 2020. Due to COVID-19 pandemic the conference was held virtually. The 125 revised full papers were carefully selected from 354 submissions. The papers focus on simulation methods, simulation techniques, simulation software, simulation performance, modeling formalisms, simulation verification and widely used frameworks.
Automated Machine Learning with AutoKeras
Create better and easy-to-use deep learning models with AutoKerasKey Features: Design and implement your own custom machine learning models using the features of AutoKerasLearn how to use AutoKeras for techniques such as classification, regression, and sentiment analysisGet familiar with advanced concepts as multi-modal, multi-task, and search space customizationBook Description: AutoKeras is an AutoML open-source software library that provides easy access to deep learning models. If you are looking to build deep learning model architectures and perform parameter tuning automatically using AutoKeras, then this book is for you.This book teaches you how to develop and use state-of-the-art AI algorithms in your projects. It begins with a high-level introduction to automated machine learning, explaining all the concepts required to get started with this machine learning approach. You will then learn how to use AutoKeras for image and text classification and regression. As you make progress, you'll discover how to use AutoKeras to perform sentiment analysis on documents. This book will also show you how to implement a custom model for topic classification with AutoKeras. Toward the end, you will explore advanced concepts of AutoKeras such as working with multi-modal data and multi-task, customizing the model with AutoModel, and visualizing experiment results using AutoKeras Extensions.By the end of this machine learning book, you will be able to confidently use AutoKeras to design your own custom machine learning models in your company.What You Will Learn: Set up a deep learning workstation with TensorFlow and AutoKerasAutomate a machine learning pipeline with AutoKerasCreate and implement image and text classifiers and regressors using AutoKerasUse AutoKeras to perform sentiment analysis of a text, classifying it as negative or positiveLeverage AutoKeras to classify documents by topicsMake the most of AutoKeras by using its most powerful extensionsWho this book is for: This book is for machine learning and deep learning enthusiasts who want to apply automated ML techniques to their projects. Prior basic knowledge of Python programming and machine learning is expected to get the most out of this book.
Becoming a Data Head
"Turn yourself into a Data Head. You'll become a more valuable employee and make your organization more successful."Thomas H. Davenport, Research Fellow, Author of Competing on Analytics, Big Data @ Work, and The AI Advantage You've heard the hype around data - now get the facts. In Becoming a Data Head: How to Think, Speak, and Understand Data Science, Statistics, and Machine Learning, award-winning data scientists Alex Gutman and Jordan Goldmeier pull back the curtain on data science and give you the language and tools necessary to talk and think critically about it. You'll learn how to: Think statistically and understand the role variation plays in your life and decision making Speak intelligently and ask the right questions about the statistics and results you encounter in the workplace Understand what's really going on with machine learning, text analytics, deep learning, and artificial intelligence Avoid common pitfalls when working with and interpreting data Becoming a Data Head is a complete guide for data science in the workplace: covering everything from the personalities you'll work with to the math behind the algorithms. The authors have spent years in data trenches and sought to create a fun, approachable, and eminently readable book. Anyone can become a Data Head--an active participant in data science, statistics, and machine learning. Whether you're a business professional, engineer, executive, or aspiring data scientist, this book is for you.
Responsible Data Science
Explore the most serious prevalent ethical issues in data science with this insightful new resource The increasing popularity of data science has resulted in numerous well-publicized cases of bias, injustice, and discrimination. The widespread deployment of "Black box" algorithms that are difficult or impossible to understand and explain, even for their developers, is a primary source of these unanticipated harms, making modern techniques and methods for manipulating large data sets seem sinister, even dangerous. When put in the hands of authoritarian governments, these algorithms have enabled suppression of political dissent and persecution of minorities. To prevent these harms, data scientists everywhere must come to understand how the algorithms that they build and deploy may harm certain groups or be unfair. Responsible Data Science delivers a comprehensive, practical treatment of how to implement data science solutions in an even-handed and ethical manner that minimizes the risk of undue harm to vulnerable members of society. Both data science practitioners and managers of analytics teams will learn how to: Improve model transparency, even for black box models Diagnose bias and unfairness within models using multiple metrics Audit projects to ensure fairness and minimize the possibility of unintended harm Perfect for data science practitioners, Responsible Data Science will also earn a spot on the bookshelves of technically inclined managers, software developers, and statisticians.
Conceptual Data Modeling and Database Design: A Fully Algorithmic Approach, Volume 1
This new book aims to provide to both beginners and experts with a completely algorithmic approach to data analysis and conceptual modeling, database design, implementation, and tuning, starting from vague and incomplete customer requests and ending with IBM DB/2, Oracle, MySQL, MS SQL Server, or Access based software applications. A rich panoply of solutions to actual useful data sub-universes (e.g. business, university, public and home library, geography, history, etc.) is provided, constituting a powerful library of examples. Four data models are presented and used: the graphical Entity-Relationship, the mathematical EMDM, the physical Relational, and the logical deterministic deductive Datalogones. For each one of them, best practice rules, algorithms, and the theory beneath are clearly separated. Four case studies, from a simple public library example, to a complex geographical study are fully presented, on all needed levels.Several dozens of real life exercises are proposed, out of which at least one per chapter is completely solved. Both major historical and up-to-date references are provided for each of the four data models considered.The book provides a library of useful solutions to real-life problems and provides valuable knowledge on data analysis and modeling, database design, implementation, and fine tuning.
Computing Predictive Analytics, Business Intelligence, and Economics
This volume brings together research and system designs that address the scientific basis and the practical systems design issues that support areas ranging from intelligent business interfaces and predictive analytics to economics modeling. Applications for management science and IT have been of interest areas for business schools and computing experts during recent years. Among the areas that are being treated are modern analytics, heterogeneous computing, business intelligence, ERP (enterprise resource planning), and decision science. Consumers have been pledging their love for data visualizations for a while now, and data is the area being explored, such as B2B and EC (E-commerce), E-business and the Intelligent Web, CRM (customer relationship management), infrastructures, and more. The digitization implications of these many new applications are described and explored in this informative volume.One of BookAuthority's Best New Analytics Books to Read in 2020!
Hci in Games: Experience Design and Game Mechanics
This two-volume set LNCS 12789 and 12790 constitutes the refereed proceedings of the Third International Conference on HCI in Games, HCI-Games 2021, held as part of the 23rd International Conference, HCI International 2021, which took place in July 2021. Due to COVID-19 pandemic the conference was held virtually. The total of 1276 papers and 241 posters included in the 39 HCII 2021 proceedings volumes was carefully reviewed and selected from 5222 submissions. The papers of HCI-Games 2021, Part I, are organized in topical sections named: Experience Design in Games; User Engagement and Game Impact; Game Mechanics.
Contemporary Issues in Group Decision and Negotiation
This book constitutes the refereed proceedings of the 21st International Conference on Group Decision and Negotiation, GDN 2021, which was planned to be held in Toronto, ON, Canada, during June 6-10, 2021. The conference was held virtually due to the COVID-19 pandemic.The field of Group Decision and Negotiation focuses on decision processes with at least two participants and a common goal but conflicting individual goals. Research areas of Group Decision and Negotiation include electronic negotiations, experiments, the role of emotions in group decision and negotiations, preference elicitation and decision support for group decisions and negotiations, and conflict resolution principles. The 12 full papers presented in this volume were carefully reviewed and selected from 74 submissions. They were organized in topical sections as follows: pandemic responses; preference modeling for group decision and negotiation; conflict resolution; and collaborative decision making processes.
Advances in Intelligent Data Analysis XIX
This book constitutes the proceedings of the 19th International Symposium on Intelligent Data Analysis, IDA 2021, which was planned to take place in Porto, Portugal. Due to the COVID-19 pandemic the conference was held online during April 26-28, 2021.The 35 papers included in this book were carefully reviewed and selected from 113 submissions. The papers were organized in topical sections named: modeling with neural networks; modeling with statistical learning; modeling language and graphs; and modeling special data formats.
Advances in Enterprise Engineering XIV
This book constitutes the proceedings of the 10th Enterprise Engineering Working Conference, EEWC 2020, which was planned to take place in Bozen-Bolzano, Italy, and had to change to an online event due to the COVID 19 pandemic. The online event took place on September 28, 2020, October 19, 2020, and November 9-10, 2020.EEWC aims at addressing the challenges that modern and complex enterprises are facing in a rapidly changing world. The participants of the working conference share a belief that dealing with these challenges requires rigorous and scientific solutions, focusing on the design and engineering of enterprises. The goal of EEWC is to stimulate interaction between the different stakeholders, scientists as well as practitioners, interested in making Enterprise Engineering a reality. The 8 full papers and 2 short papers presented in this volume were carefully reviewed and selected from 23 submissions. The volume also contains 3 keynote papers in full paper length. Thepapers were organized in topical sections as follows: formal approaches and modeling; the DEMO modeling language; and enterprise engineering practice.
Digital Fluency
If you are curious about the basics of artificial intelligence, blockchain technology, and quantum computing as key enablers for digital transformation and innovation, Digital Fluency is your handy guide. The real-world applications of these cutting-edge technologies are expanding rapidly, and your daily life will continue to be affected by each of them. There is no better time than now to get started and become digitally fluent.You need not have previous knowledge of these versatile technologies, as author Volker Lang will expertly guide you through this digital age. He illustrates key concepts and applications in numerous practical examples and more than 48 catchy figures throughout Digital Fluency. The end of each chapter presents you with a helpful implementation checklist of central lessons before proceeding to the next. This book gets to the heart of digital buzzwords and concepts, and tells you what they truly mean. Breaking down topics such as automated driving and intelligent robotics powered by artificial intelligence, blockchain-based cryptocurrencies and smart contracts, drug development and optimization of financial investment portfolios by quantum computing, and more is imperative to being ready for what the future of industry holds. Whether your own digital transformation journey takes place within your private or public organization, your studies, or your individual household, Digital Fluency maps out a concrete digital action plan for all of your technology and innovation strategy needs.What You Will Learn Gain guidance in the digital age without requiring any previous knowledge about digital technologies and digital transformationGet acquainted with the most popular current and prospective applications of artificial intelligence, blockchain technology, and quantum computing across a wide range of industries including healthcare, financial services, and the automobile industryBecome familiar with the digital innovation models of Amazon, Google, Microsoft, IBM, and other world-leading organizations Implement your own digital transformation successfully along the eight core dimensions of a concrete digital action planWho This Book Is ForThought-leaders, business executives and industry strategists, management and strategy consultants, politicians and policy makers, entrepreneurs, financial analysts, investors and venture capitalists, students and research scientists, as well as general readers, who want to become digitally fluent.
Analysis of Images, Social Networks and Texts
This book constitutes revised selected papers from the 9th International Conference on Analysis of Images, Social Networks and Texts, AIST 2020, held during October 15-16, 2020. The conference was planned to take place in Moscow, Russia, but changed to an online format due to the COVID-19 pandemic.The 27 full papers and 4 short papers presented in this volume were carefully reviewed and selected from a total of 108 qualified submissions. The papers are organized in topical sections as follows: invited papers; natural language processing; computer vision; social network analysis; data analysis and machine learning; theoretical machine learning and optimization; and process mining.
Decision Support Systems XI: Decision Support Systems, Analytics and Technologies in Response to Global Crisis Management
This book constitutes the proceedings of the 7th International Conference on Decision Support Systems Technologies, ICDSST 2021, held during May 26-28, 2021. The conference was planned to take place in Loughborough, UK, and changed to an online format due to the COVID-19 pandemic.The EWG-DSS series of International Conference on Decision Support System Technology (ICDSST) is planned to consolidate the tradition of annual events organized by the EWG-DSS in offering a platform for European and international DSS communities, comprising the academic and industrial sectors, to present state-of-the-art DSS research and developments, to discuss current challenges that surround decision-making processes, to exchange ideas about realistic and innovative solutions, and to co-develop potential business opportunities. The main aim of this year's conference is to investigate the role DSS and related technologies can play in mitigating the impact of pandemics and post-crisis recovery. The 10 papers presented in this volume were carefully reviewed and selected from 44 submissions. They were organized in two topical sections named: multiple criteria approaches and advances in decision support systems' technologies and methods.
Sustainable Energy for Smart Cities
This book constitutes the refereed post-conference proceedings of the Second EAI International Conference on Sustainable Energy for Smart Cities, SESC 2020, held in Portugal in December 2020. The conference was framed within the 6th Annual Smart City 360簞 Summit. Due to COVID-19 pandemic the conferences were held virtually.The 13 revised full papers were carefully reviewed and selected from 27 submissions. They present multidisciplinary scientific results toward answering the complex technological problems of emergent Smart Cities. The subjects related to sustainable energy, framed with the scope of smart cities and addressed along with the SESC 2020 conference, are crucial to guarantee an equilibrium among economic growth and environmental sustainability, as well as to contribute to reducing the impact of climate change.
Principles of Parallel Scientific Computing
New insight in many scientific and engineering fields is unthinkable without the use of numerical simulations running efficiently on modern computers. The faster we get new results, the bigger and accurate are the problems that we can solve. It is the combination of mathematical ideas plus efficient programming that drives the progress in many disciplines. Future champions in the area thus will have to be qualified in their application domain, they will need a profound understanding of some mathematical ideas, and they need the skills to deliver fast code. The present textbook targets students which have programming skills already and do not shy away from mathematics, though they might be educated in computer science or an application domain. It introduces the basic concepts and ideas behind applied mathematics and parallel programming that we need to write numerical simulations for today's multicore workstations. Our intention is not to dive into one particular applicationdomain or to introduce a new programming language - we lay the generic foundations for future courses and projects in the area. The text is written in an accessible style which is easy to digest for students without years and years of mathematics education. It values clarity and intuition over formalism, and uses a simple N-body simulation setup to illustrate basic ideas that are of relevance in various different subdomains of scientific computing. Its primary goal is to make theoretical and paradigmatic ideas accessible to undergraduate students and to bring the fascination of the field across.
iPhone 11
Are you looking to tap into the hidden potential of the iPhone 11? The latest phones from Apple are loaded with tons of amazing features. In order to unlock its power, you need an informative book.That's where this guide comes in. With the swift changes in technology, you'll need a guide that can keep up with the times, is accurate, and one that can stand side by side with the devices/technologies that it explores.In this eBook, here's what you'll uncover: Advanced facial recognition features that are state-of-the-art and can be used in many secure waysHow the phone's durable, stunning and top-notch construction provides so many benefitsThe excellent "Portait Mode" feature with Apple's thoroughly designed camera lensMore about its innovative A13 Bionic CPU and how it increases the phone's speedA step-by-step guide to use your iPhone to its fullestHow to finish up your iPhone 11 settingsHow it stacks up compare to other iPhonesMore about its powerful iOS platformAnd much more!With so many great features of this phone, you'll need a great resource in order to show you how to utilize so many of these enhancements. Let this book be your guide!What are you waiting for? Grab your own copy today!
Database Systems for Advanced Applications
The three-volume set LNCS 12681-12683 constitutes the proceedings of the 26th International Conference on Database Systems for Advanced Applications, DASFAA 2021, held in Taipei, Taiwan, in April 2021. The total of 156 papers presented in this three-volume set was carefully reviewed and selected from 490 submissions. The topic areas for the selected papers include information retrieval, search and recommendation techniques; RDF, knowledge graphs, semantic web, and knowledge management; and spatial, temporal, sequence, and streaming data management, while the dominant keywords are network, recommendation, graph, learning, and model. These topic areas and keywords shed the light on the direction where the research in DASFAA is moving towards. Due to the Corona pandemic this event was held virtually.
Database Systems for Advanced Applications
The three-volume set LNCS 12681-12683 constitutes the proceedings of the 26th International Conference on Database Systems for Advanced Applications, DASFAA 2021, held in Taipei, Taiwan, in April 2021. The total of 156 papers presented in this three-volume set was carefully reviewed and selected from 490 submissions. The topic areas for the selected papers include information retrieval, search and recommendation techniques; RDF, knowledge graphs, semantic web, and knowledge management; and spatial, temporal, sequence, and streaming data management, while the dominant keywords are network, recommendation, graph, learning, and model. These topic areas and keywords shed the light on the direction where the research in DASFAA is moving towards. Due to the Corona pandemic this event was held virtually.
Parallel Distributed Processing, Volume 1
What makes people smarter than computers? These volumes by a pioneering neurocomputing group suggest that the answer lies in the massively parallel architecture of the human mind. They describe a new theory of cognition called connectionism that is challenging the idea of symbolic computation that has traditionally been at the center of debate in theoretical discussions about the mind. The authors' theory assumes the mind is composed of a great number of elementary units connected in a neural network. Mental processes are interactions between these units which excite and inhibit each other in parallel rather than sequential operations. In this context, knowledge can no longer be thought of as stored in localized structures; instead, it consists of the connections between pairs of units that are distributed throughout the network. Volume 1 lays the foundations of this exciting theory of parallel distributed processing, while Volume 2 applies it to a number of specific issues in cognitive science and neuroscience, with chapters describing models of aspects of perception, memory, language, and thought.
iPhone 11 Pro Max Guide
Have you recently got your iPhone 11 Pro Max, but do not know how to operate and enjoy its features to its fullest? If Yes, then Keep Reading!iPhone 11 Pro Max entered the market with the iPhone 11 and iPhone 11 Pro. Apple launched three amazing iPhones in 2019. Apart from having iOS 13 as its operating system, the main highlight of the iPhone 11 Pro Max is its three-camera system, which is more than enough to own it. One can feel overwhelming because of the features that iOS 13 brings with iPhone 11 Pro Max. This book will help you in exploring all those features. It is a step-by-step guide for you to get started and master the functions of your phone. The design, technology, better sound, three cameras, and enhanced battery life of iPhone 11 Pro Max offer an exciting experience to have by using this phone.In this book, you will find out how to use your favorite apps like ebooks, music, games, and much more within no time. This book has some solutions to your problems that you might face during the troubleshooting for. You can find difficulty and face some troubleshooting while using some apps with this latest technology. This book has some of the best solutions to make things easy and much more straightforward for you. You can utilize this book to learn from getting started with your iPhone 11 Pro Max to mastering some advanced settings and tricks.In this book, you will learn: A complete step by step procedure to set up and operate your iPhone 11 Pro Max.How to restore or transfer data from another device.A detailed account of the fantastic new features in the iPhone 11 Pro Max. A step-by-step guide to install and uninstall apps on your phone.How to activate Dark Mode.How to make the best out of Siri in your iPhone 11 Pro Max.How to use the Camera App of iPhone 11 Pro Max. The functions of three lenses and their best use. Track menstrual cycle in Health App. Some useful tips to enjoy iOS 13 features. And much more!All the above tips to familiarize yourself with the use of iPhone 11 Pro Max. So, what are you waiting for? Grab your own copy today!
SQL Server Reporting Services Crash Course
This book is a straightforward and practical crash course with a large number of colorful screenshots that even someone with little experience in the field will find comprehendible. It will guide and provide you with a streamlined resource on how to develop reports using Business Intelligence tools, SQL Server Reporting Services. Through reading this easy-to-understand book, you will also learn how to add Cascade Parameter, Expressions, Document mapping, create Sub Reports, link other reports within the main report, create custom Report Definition Language, FMTONLY ON/OFF as well as convert an image to BLOB image. For those of you who purchased this book, thank you from the bottom of my heart! I hope you can sense that I've poured my heart and soul into writing this book and creating a resource that will broaden and sharpen your "toolbox" of skills. I hope you enjoy it and find it useful.
Smart Technologies for Precision Assembly
This open access book constitutes the refereed post-conference proceedings of the 9th IFIP WG 5.5 International Precision Assembly Seminar, IPAS 2020, held virtually in December 2020.The 16 revised full papers and 10 revised short papers presented together with 1 keynote paper were carefully reviewed and selected from numerous submissions. The papers address topics such as assembly design and planning; assembly operations; assembly cells and systems; human centred assembly; and assistance methods in assembly.
Infrastructure-As-Code Automation Using Terraform, Packer, and Vault
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. 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. 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. What You Will Learn Get an overview of the architecture of Terraform, Vault, Packer, Nomad, and ConsulFollow hands-on steps for enabling Terraform, Vault, Packer, Nomad, and ConsulAutomate various services on the public cloud, including AWS, Azure, and GCP Who This Book Is For Developers, architects, and administrators who want to learn about infrastructure-as-code automation.
Mongodb Performance Tuning
Use this fast and complete guide to optimize the performance of MongoDB databases and the applications that depend on them. You will be able to turbo-charge the performance of your MongoDB applications to provide a better experience for your users, reduce your running costs, and avoid application growing pains. MongoDB is the world's most popular document database and the foundation for thousands of mission-critical applications. This book helps you get the best possible performance from MongoDB.MongoDB Performance Tuning takes a methodical and comprehensive approach to performance tuning that begins with application and schema design and goes on to cover optimization of code at all levels of an application. The book also explains how to configure MongoDB hardware and cluster configuration for optimal performance. The systematic approach in the book helps you treat the true causes of performance issues and get the best return on your tuninginvestment. Even when you're under pressure and don't know where to begin, simply follow the method in this book to set things right and get your MongoDB performance back on track. What You Will LearnApply a methodical approach to MongoDB performance tuningUnderstand how to design an efficient MongoDB applicationOptimize MongoDB document design and indexing strategiesTune MongoDB queries, aggregation pipelines, and transactionsOptimize MongoDB server resources: CPU, memory, diskConfigure MongoDB Replica sets and Sharded clusters for optimal performanceWho This Book Is ForDevelopers and administrators of high-performance MongoDB applications who want to be sure they are getting the best possible performance from their MongoDB system. For developers who wish to create applications that are fast, scalable, and cost-effective. For administrators who want to optimize their MongoDB server and hardware configuration.
Machine Learning Automation with TPOT
Discover how TPOT can be used to handle automation in machine learning and explore the different types of tasks that TPOT can automateKey Features: Understand parallelism and how to achieve it in Python.Learn how to use neurons, layers, and activation functions and structure an artificial neural network.Tune TPOT models to ensure optimum performance on previously unseen data.Book Description: The automation of machine learning tasks allows developers more time to focus on the usability and reactivity of the software powered by machine learning models. TPOT is a Python automated machine learning tool used for optimizing machine learning pipelines using genetic programming. Automating machine learning with TPOT enables individuals and companies to develop production-ready machine learning models cheaper and faster than with traditional methods.With this practical guide to AutoML, developers working with Python on machine learning tasks will be able to put their knowledge to work and become productive quickly. You'll adopt a hands-on approach to learning the implementation of AutoML and associated methodologies. Complete with step-by-step explanations of essential concepts, practical examples, and self-assessment questions, this book will show you how to build automated classification and regression models and compare their performance to custom-built models. As you advance, you'll also develop state-of-the-art models using only a couple of lines of code and see how those models outperform all of your previous models on the same datasets.By the end of this book, you'll have gained the confidence to implement AutoML techniques in your organization on a production level.What You Will Learn: Get to grips with building automated machine learning modelsBuild classification and regression models with impressive accuracy in a short timeDevelop neural network classifiers with AutoML techniquesCompare AutoML models with traditional, manually developed models on the same datasetsCreate robust, production-ready modelsEvaluate automated classification models based on metrics such as accuracy, recall, precision, and f1-scoreGet hands-on with deployment using Flask-RESTful on localhostWho this book is for: Data scientists, data analysts, and software developers who are new to machine learning and want to use it in their applications will find this book useful. This book is also for business users looking to automate business tasks with machine learning. Working knowledge of the Python programming language and beginner-level understanding of machine learning are necessary to get started.
Web and Big Data. Apweb-Waim 2020 International Workshops
This book constitutes revised selected papers from the workshops of the 4th Asia-Pacific Web and Web-Age Information Management International Joint Conference on Web and Big Data, APWeb-WAIM 2020: The Third International Workshop on Knowledge Graph Management and Applications, KGMA 2020; The Second International Workshop on Semi-structured Big Data Management and Applications, SemiBDMA 2020, and The First International Workshop on Deep Learning in Large-scale Unstructured Data Analytics, DeepLUDA 2020, held in Tianjin, China, in September 2020. Due to the COVID-19 pandemic the conference was held online. The 13 papers were thoroughly reviewed and selected from the numerous submissions and present recent research on the theory, design, and implementation of data management systems.
Mediterranean Forum - Data Science Conference
This book constitutes selected and revised papers from the First Mediterranean Forum - Data Science Conference, MeFDATA 2020, held in Sarajevo, Bosnia and Herzegovina, in October 2020. The 11 papers presented were carefully reviewed and selected from the 26 qualified submissions. The papers are organized in the topical sections on human behaviour and pandemic; applications in medicine; industrial applications; natural language processing.
Scalable Data Streaming with Amazon Kinesis
Explore Kinesis managed services such as Kinesis Data Streams, Kinesis Data Analytics, Kinesis Data Firehose, and Kinesis Video Streams with the help of practical use casesKey Features: Get well versed with the capabilities of Amazon KinesisExplore the monitoring, scaling, security, and deployment patterns of various Amazon Kinesis servicesLearn how other Amazon Web Services and third-party applications such as Splunk can be used as destinations for Kinesis dataBook Description: Amazon Kinesis is a collection of secure, serverless, durable, and highly available purpose-built data streaming services. This data streaming service provides APIs and client SDKs that enable you to produce and consume data at scale.Scalable Data Streaming with Amazon Kinesis begins with a quick overview of the core concepts of data streams, along with the essentials of the AWS Kinesis landscape. You'll then explore the requirements of the use case shown through the book to help you get started and cover the key pain points encountered in the data stream life cycle. As you advance, you'll get to grips with the architectural components of Kinesis, understand how they are configured to build data pipelines, and delve into the applications that connect to them for consumption and processing. You'll also build a Kinesis data pipeline from scratch and learn how to implement and apply practical solutions. Moving on, you'll learn how to configure Kinesis on a cloud platform. Finally, you'll learn how other AWS services can be integrated into Kinesis. These services include Redshift, Dynamo Database, AWS S3, Elastic Search, and third-party applications such as Splunk.By the end of this AWS book, you'll be able to build and deploy your own Kinesis data pipelines with Kinesis Data Streams (KDS), Kinesis Data Firehose (KFH), Kinesis Video Streams (KVS), and Kinesis Data Analytics (KDA).What You Will Learn: Get to grips with data streams, decoupled design, and real-time stream processingUnderstand the properties of KFH that differentiate it from other Kinesis servicesMonitor and scale KDS using CloudWatch metricsSecure KDA with identity and access management (IAM)Deploy KVS as infrastructure as code (IaC)Integrate services such as Redshift, Dynamo Database, and Splunk into KinesisWho this book is for: This book is for solutions architects, developers, system administrators, data engineers, and data scientists looking to evaluate and choose the most performant, secure, scalable, and cost-effective data streaming technology to overcome their data ingestion and processing challenges on AWS. Prior knowledge of cloud architectures on AWS, data streaming technologies, and architectures is expected.
Digital Manufacturing and Assembly Systems in Industry 4.0
Manufacturing, like other industries, is rising to the challenges imposed by aggressive consumer demands and the need for cost-effective processing that delivers quality in the fastest possible time. Fierce competition means that keeping abreast of new developments and applications in technology is essential if companies are to meet demands profitably and keep ahead of competitors. This book investigates the design and management of digital manufacturing and assembly systems for an efficient, flexible, and modular production of customized products using the I40 (industry 4.0)-enabling technologies. This book will also provide case studies covering modeling, simulation, and optimization. eBook includes color figures. Discusses how the advancement of data communication and storage through the Internet of Things (IoT) opens the possibilities of connecting sensors, robots, and devices Sheds light on how the human role in industry is decreasing due to the development of connected manufacturing floors, allowing them to take more control over the manufacturing processes, decisions, and even maintenance Covers the benefits from exploiting digital manufacturing, manufacturing enterprises, and what they expect to achieve Explains the important roles that modeling, simulation, and optimization play Investigates the design and management of digital manufacturing and assembly systems for an efficient, flexible, and modular production of customized products exploiting the I40 (industry 4.0)-enabling technologies
Practical Guide to Large Database Migration
It is a major challenge to migrate very large databases from one system, say for example, to transfer critical data from Oracle to SQL Server. One has to consider several issues such as loss of data being transferred, the security of the data, the cost and effort, technical aspects of the software involved, etc. There a very few books that provide practical tools and the methodology to migrate data from one vendor to another. This book introduces the concepts in database migration with large sample databases. It provides step by step guides and screenshots for database migration tools. Many examples are shown for migrating Oracle, SQL Server and MySQL databases.
Machine Learning for Computer and Cyber Security
While Computer Security is a broader term which incorporates technologies, protocols, standards and policies to ensure the security of the computing systems including the computer hardware, software and the information stored in it, Cyber Security is a specific, growing field to protect computer networks (offline and online) from unauthorized access, botnets, phishing scams, etc. Machine learning is a branch of Computer Science which enables computing machines to adopt new behaviors on the basis of observable and verifiable data and information. It can be applied to ensure the security of the computers and the information by detecting anomalies using data mining and other such techniques.This book will be an invaluable resource to understand the importance of machine learning and data mining in establishing computer and cyber security. It emphasizes important security aspects associated with computer and cyber security along with the analysis of machine learning and data mining based solutions. The book also highlights the future research domains in which these solutions can be applied. Furthermore, it caters to the needs of IT professionals, researchers, faculty members, scientists, graduate students, research scholars and software developers who seek to carry out research and develop combating solutions in the area of cyber security using machine learning based approaches. It is an extensive source of information for the readers belonging to the field of Computer Science and Engineering, and Cyber Security professionals.Key Features: This book contains examples and illustrations to demonstrate the principles, algorithms, challenges and applications of machine learning and data mining for computer and cyber security.It showcases important security aspects and current trends in the field.It provides an insight of the future research directions in the field.Contents of this book help to prepare the students for exercising better defense in terms of understanding the motivation of the attackers and how to deal with and mitigate the situation using machine learning based approaches in better manner.
Handbook of Iot and Big Data
This multi-contributed handbook focuses on the latest workings of IoT (internet of Things) and Big Data. As the resources are limited, it's the endeavor of the authors to support and bring the information into one resource. The book is divided into 4 sections that covers IoT and technologies, the future of Big Data, algorithms, and case studies showing IoT and Big Data in various fields such as health care, manufacturing and automation.FeaturesFocuses on the latest workings of IoT and Big Data Discusses the emerging role of technologies and the fast-growing market of Big Data Covers the movement toward automation with hardware, software, and sensors, and trying to save on energy resources Offers the latest technology on IoT Presents the future horizons on Big Data
Database Systems for Advanced Applications. Dasfaa 2021 International Workshops
This volume constitutes the papers of several workshops which were held in conjunction with the 26th International Conference on Database Systems for Advanced Applications, DASFAA 2021, held in Taipei, Taiwan, in April 2021. The 29 revised full papers presented in this book were carefully reviewed and selected from 84 submissions. DASFAA 2021 presents the following five workshops: 6th International Workshop on Big Data Quality Management (BDQM 2021)5th International Workshop on Graph Data Management and Analysis (GDMA 2021) First International Workshop on Machine Learning and Deep Learning for Data Security Applications (MLDLDSA 2021)6th International Workshop on Mobile Data Management, Mining, and Computing on Social Network (MobiSocial 2021)2021 International Workshop on Mobile Ubiquitous Systems and Technologies (MUST 2021)Due to the Corona pandemic this event was held virtually.
Big Data
This book constitutes the proceedings of the 8th CCF Conference on Big Data, BigData 2020, held in Chongqing, China, in October 2020.The 16 full papers presented in this volume were carefully reviewed and selected from 65 submissions. They present recent research on theoretical and technical aspects on big data, as well as on digital economy demands in big data applications.
Process Mining Workshops
This book constitutes revised selected papers from the International Workshops held at the Second International Conference on Process Mining, ICPM 2020, which took place during October 4-9, 2020. The conference was planned to take place in Padua, Italy, but had to be held online due to the COVID-19 pandemic.The conference focuses on the area of process mining research and practice, including theory, algorithmic challenges, and applications. The co-located workshops provided a forum for novel research ideas. The 29 papers included in this volume were carefully reviewed and selected from 59 submissions. They stem from the following workshops: 1st International Workshop on Event Data and Behavioral Analytics (EDBA) 1st International Workshop on Leveraging Machine Learning in Process Mining (ML4PM) 1st International Workshop on Streaming Analytics for Process Mining (SA4PM'20) 5th International Workshop on Process Querying, Manipulation, and Intelligence (PQMI) 3rd International Workshop on Process-Oriented Data Science for Healthcare (PODS4H) 1st International Workshop on Trust and Privacy in Process Analytics (TPPA)
The Data Journalism Handbook
The Data Journalism Handbook: Towards a Critical Data Practice provides a rich and panoramic introduction to data journalism, combining both critical reflection and practical insight. It offers a diverse collection of perspectives on how data journalism is done around the world and the broader consequences of datafication in the news, serving as both a textbook and a sourcebook for this emerging field. With more than 50 chapters from leading researchers and practitioners of data journalism, it explores the work needed to render technologies and data productive for journalistic purposes. It also gives a behind the scenes look at the social lives of data sets, data infrastructures, and data stories in newsrooms, media organizations, start-ups, civil society organizations and beyond. The book includes sections on doing issues with data, assembling data, working with data, experiencing data, investigating data, platforms and algorithms, organizing data journalism, learning data journalism together and situating data journalism.
Evolutionary Computation in Combinatorial Optimization
This book constitutes the refereed proceedings of the 21st European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2021, held as part of Evo*2021, as Virtual Event, in April 2021, co-located with the Evo*2021 events: EvoMUSART, EvoApplications, and EuroGP. The 14 revised full papers presented in this book were carefully reviewed and selected from 42 submissions. They cover a wide spectrum of topics, ranging from the foundations of evolutionary algorithms and other search heuristics to their accurate design and application to combinatorial optimization problems. Fundamental and methodological aspects deal with runtime analysis, the structural properties of fitness landscapes, the study of core components of metaheuristics, the clever design of their search principles, and their careful selection and configuration. Applications cover problem domains such as scheduling, routing, search-based software engineering and general graph problems. The range of topics covered in this volume reflects the current state of research in the fields of evolutionary computation and combinatorial optimization.
Population Genetics with R
Population genetics is an inherently quantitative discipline, yet often focuses upon abstract concepts which can be difficult to conceptualize and appropriately visualize at first glance. This book focuses on applying the hugely popular R software specifically to the field, offering an accessible, step-by-step guide to tackling the challenges of achieving effective data interpretation and summary. The authors adopt an engaging "learning by doing" approach that will enable readers to develop an intuitive understanding of key population genetics concepts through the use of R. Beginning with the groundwork of installing and using R (including CRAN and the RStudio IDE), the book works through the use of basic commands for data manipulation. An introduction to basic terminology in population genetics follows, clearly explaining how these fundamental assumptions can provide insights and form basic inferences for real populations. The focus then moves onto statistical tests including writing and running algorithms as functions. Subsequent chapters examine genetic variation, adaptation, and natural selection as well as different approaches to population differences. Importantly, the accompanying set of practical exercises demonstrate that implementing all of these concepts via programming can actually help greatly in understanding them, even if they may at first seem insurmountably complex. Finally, this accessible textbook points the way forwards to other key concepts that are important to understanding modern day population genetics research (in particular coalescent theory) and offers the reader useful launching points for further learning. Population Genetics with R is aimed at students ranging from undergraduate to postgraduate level in the fields of population genetics, ecology, evolutionary biology, conservation genetics, computational biology, and biostatistics.
Population Genetics with R
Population genetics is an inherently quantitative discipline, yet often focuses upon abstract concepts which can be difficult to conceptualize and appropriately visualize at first glance. This book focuses on applying the hugely popular R software specifically to the field, offering an accessible, step-by-step guide to tackling the challenges of achieving effective data interpretation and summary. The authors adopt an engaging "learning by doing" approach that will enable readers to develop an intuitive understanding of key population genetics concepts through the use of R. Beginning with the groundwork of installing and using R (including CRAN and the RStudio IDE), the book works through the use of basic commands for data manipulation. An introduction to basic terminology in population genetics follows, clearly explaining how these fundamental assumptions can provide insights and form basic inferences for real populations. The focus then moves onto statistical tests including writing and running algorithms as functions. Subsequent chapters examine genetic variation, adaptation, and natural selection as well as different approaches to population differences. Importantly, the accompanying set of practical exercises demonstrate that implementing all of these concepts via programming can actually help greatly in understanding them, even if they may at first seem insurmountably complex. Finally, this accessible textbook points the way forwards to other key concepts that are important to understanding modern day population genetics research (in particular coalescent theory) and offers the reader useful launching points for further learning. Population Genetics with R is aimed at students ranging from undergraduate to postgraduate level in the fields of population genetics, ecology, evolutionary biology, conservation genetics, computational biology, and biostatistics.
Physics of Data Science and Machine Learning
Physics of Data Science and Machine Learning links fundamental concepts of physics to data science, machine learning, and artificial intelligence for physicists looking to integrate these techniques into their work. This book is written explicitly for physicists, marrying quantum and statistical mechanics with modern data mining, data science, and machine learning. It also explains how to integrate these techniques into the design of experiments, while exploring neural networks and machine learning, building on fundamental concepts of statistical and quantum mechanics. This book is a self-learning tool for physicists looking to learn how to utilize data science and machine learning in their research. It will also be of interest to computer scientists and applied mathematicians, alongside graduate students looking to understand the basic concepts and foundations of data science, machine learning, and artificial intelligence. Although specifically written for physicists, it will also help provide non-physicists with an opportunity to understand the fundamental concepts from a physics perspective to aid in the development of new and innovative machine learning and artificial intelligence tools. Key Features: Introduces the design of experiments and digital twin concepts in simple lay terms for physicists to understand, adopt, and adapt. Free from endless derivations; instead, equations are presented and it is explained strategically why it is imperative to use them and how they will help in the task at hand. Illustrations and simple explanations help readers visualize and absorb the difficult-to-understand concepts. Ijaz A. Rauf is an adjunct professor at the School of Graduate Studies, York University, Toronto, Canada. He is also an associate researcher at Ryerson University, Toronto, Canada and president of the Eminent-Tech Corporation, Bradford, ON, Canada.
Physics of Data Science and Machine Learning
Physics of Data Science and Machine Learning links fundamental concepts of physics to data science, machine learning, and artificial intelligence for physicists looking to integrate these techniques into their work. This book is written explicitly for physicists, marrying quantum and statistical mechanics with modern data mining, data science, and machine learning. It also explains how to integrate these techniques into the design of experiments, while exploring neural networks and machine learning, building on fundamental concepts of statistical and quantum mechanics. This book is a self-learning tool for physicists looking to learn how to utilize data science and machine learning in their research. It will also be of interest to computer scientists and applied mathematicians, alongside graduate students looking to understand the basic concepts and foundations of data science, machine learning, and artificial intelligence. Although specifically written for physicists, it will also help provide non-physicists with an opportunity to understand the fundamental concepts from a physics perspective to aid in the development of new and innovative machine learning and artificial intelligence tools. Key Features: Introduces the design of experiments and digital twin concepts in simple lay terms for physicists to understand, adopt, and adapt. Free from endless derivations; instead, equations are presented and it is explained strategically why it is imperative to use them and how they will help in the task at hand. Illustrations and simple explanations help readers visualize and absorb the difficult-to-understand concepts. Ijaz A. Rauf is an adjunct professor at the School of Graduate Studies, York University, Toronto, Canada. He is also an associate researcher at Ryerson University, Toronto, Canada and president of the Eminent-Tech Corporation, Bradford, ON, Canada.
Statistical Trend Analysis of Physically Unclonable Functions
Physically Unclonable Functions (PUFs) translate unavoidable variations in certain parameters of materials, waves, or devices into random and unique signals. They have found many applications in the Internet of Things (IoT), authentication systems, FPGA industry, several other areas in communications and related technologies, and many commercial products. Statistical Trend Analysis of Physically Unclonable Functions first presents a review on cryptographic hardware and hardware-assisted cryptography. The review highlights PUF as a mega trend in research on cryptographic hardware design. Afterwards, the authors present a combined survey and research work on PUFs using a systematic approach. As part of the survey aspect, a state-of-the-art analysis is presented as well as a taxonomy on PUFs, a life cycle, and an established ecosystem for the technology. In another part of the survey, the evolutionary history of PUFs is examined, and strategies for further research in this area are suggested. In the research side, this book presents a novel approach for trend analysis that can be applied to any technology or research area. In this method, a text mining tool is used which extracts 1020 keywords from the titles of the sample papers. Then, a classifying tool classifies the keywords into 295 meaningful research topics. The popularity of each topic is then numerically measured and analyzed over the course of time through a statistical analysis on the number of research papers related to the topic as well as the number of their citations. The authors identify the most popular topics in four different domains; over the history of PUFs, during the recent years, in top conferences, and in top journals. The results are used to present an evolution study as well as a trend analysis and develop a roadmap for future research in this area. This method gives an automatic popularity-based statistical trend analysis which eliminates the need for passing personal judgments about the direction of trends, and provides concrete evidence to the future direction of research on PUFs. Another advantage of this method is the possibility of studying a whole lot of existing research works (more than 700 in this book). This book will appeal to researchers in text mining, cryptography, hardware security, and IoT.
Heron Streaming
This book provides both a basic understanding of stream processing in general, and practical guidance for development and research with Apache Heron in particular. It delivers to developers of streaming applications basic and systematic knowledge about Heron, which is today only scattered across project documents, technique blogs and code snippets on the Web.The book is organized in four parts: Part I describes basic knowledge about stream processing, Apache Storm, and Apache Heron (Incubating), and also introduces the Heron source repository. Part II then goes into details and describes two data models to write Heron topologies and often used topology features, including stateful processing. This part is especially targeted at software developers who write topologies using Heron APIs. Next, part III describes Heron tools, including the command-line interface and the user interface, needed to manage a single topology or multiple topologies in a data center. This part is particularly aimed at operators who deploy and manage running jobs. Eventually, part IV describes the Heron source code and how to customize or extend Heron. This part is especially suggested for software engineers who would like to contribute code to the Heron repository and who are curious about Heron insights. Overall, this book aims at professionals who want to process streaming data based on Apache Heron. A basic knowledge of Java and Bash commands for Linux is assumed.
Learning Domain-Driven Design
Building software is harder than ever. As a developer, you not only have to chase ever-changing technological trends but also need to understand the business domains behind the software. This practical book provides you with a set of core patterns, principles, and practices for analyzing business domains, understanding business strategy, and, most importantly, aligning software design with its business needs. Author Vlad Khononov shows you how these practices lead to robust implementation of business logic and help to future-proof software design and architecture. You'll examine the relationship between domain-driven design (DDD) and other methodologies to ensure you make architectural decisions that meet business requirements. You'll also explore the real-life story of implementing DDD in a startup company. With this book, you'll learn how to: Analyze a company's business domain to learn how the system you're building fits its competitive strategy Use DDD's strategic and tactical tools to architect effective software solutions that address business needs Build a shared understanding of the business domains you encounter Decompose a system into bounded contexts Coordinate the work of multiple teams Gradually introduce DDD to brownfield projects
