Precisely
Bronze Medal Winner, 2024 Axiom Business Book Award, Emerging Trends / AI If you want to win an election, improve the health of a city, or thrill your customers, you're going to need precision systems--the highly engineered working arrangements of teams, processes, and technologies that put data and AI to work creating the change that leaders want, exactly how they want it. Big Tech firms like Amazon, Google, Apple, and Facebook have mastered their own precision systems, building trillion-dollar businesses using data-driven tools from mass-market "nudges" to industrial-grade recommendation systems. Precisely is the playbook for the rest of us. Zachary Tumin and Madeleine Want show how leaders in every domain are taking real-time precision systems into the marketplace, the political race, and the fight for health--from New York-Presbyterian Hospital to the New York Times, the NFL's Baltimore Ravens to BNSF Railroad, the Biden-Harris campaign to the NYPD--to reveal elusive patterns, perform a repetitive task, run a play, or tailor a message, one at a time or by the millions. Precisely provides insight that will help leaders choose the system that's right for them, decide which problem to tackle first, sell the importance of precision to stakeholders, power-up the people and the technology, and accomplish change that delivers precisely what's needed every time--and do it all responsibly.
Snowpro(tm) Core Certification Companion
This study companion helps you prepare for the SnowPro Core Certification exam. The author guides your studies so you will not have to tackle the exam by yourself. To help you track your progress, chapters in this book correspond to the exam domains as described on Snowflake's website. Upon studying the material in this book, you will have solid knowledge that should give you the best shot possible at taking and passing the exam and earning the certification you deserve. Each chapter provides explanations, instructions, guidance, tips, and other information with the level of detail that you need to prepare for the exam. You will not waste your time with unneeded detail and advanced content which is out of scope of the exam. Focus is kept on reviewing the materials and helping you become familiar with the content of the exam that is recommended by Snowflake.This Book Helps YouReview the domainsthat Snowflake specifically recommends you study in preparation for Exam COF-C02Identify gaps in your knowledge that you can study and fill in to increase your chances of passing Exam COF-C02Level up your knowledge even if not taking the exam, so you know the same material as someone who has taken the examLearn how to set up a Snowflake account and configure access according to recommended security best practicesBe capable of loading structured and unstructured data into Snowflake as well as unloading data from SnowflakeUnderstand how to apply Snowflake data protection features such as cloning, time travel, and fail safeReview Snowflake's data sharing capabilities, including data marketplace and data exchangeWho This Book Is ForThose who are planning to take the SnowPro Core Certification COF-C02 exam, and anyone who wishes to gain core expertise in implementing and migrating tothe Snowflake Data Cloud
Intelligent Transport Systems
This book constitutes the proceedings of the 6th International Conference on Intelligent Transport Systems, INTSYS 2022, which was held in Lisbon, Portugal, in December 15-16, 2022. With the globalization of trade and transportation and the consequent multi-modal solutions used, additional challenges are faced by organizations and countries. Intelligent Transport Systems make transport safer, more efficient, and more sustainable by applying information and communication technologies to all transportation modes.The 15 revised full papers in this book were selected from 45 submissions and are organized in three thematic sessions on smart city; transportation modes and AI; intelligent transportation and electric vehicles.
Information for a Better World: Normality, Virtuality, Physicality, Inclusivity
This two-volume set LNCS 13971 + 13972 constitutes the refereed proceedings of the 18th International Conference on Information for a Better World: Normality, Virtuality, Physicality, Inclusivity, held in March 2023.The 36 full papers and the 46 short papers presented in these proceedings were carefully reviewed and selected from 197 submissions. They cover topics such as: Archives and Records, Behavioral Research, Information Governance and Ethics, AI and Machine Learning, Data Science, Information and Digital literacy, Cultural Perspectives, Knowledge Management and Intellectual Capital, Social Media and Digital Networks, Libraries, Human-Computer Interaction and Technology, Information Retrieval, Community Informatics, and Digital Information Infrastructure.
Machine Learning, Optimization, and Data Science
This two-volume set, LNCS 13810 and 13811, constitutes the refereed proceedings of the 8th International Conference on Machine Learning, Optimization, and Data Science, LOD 2022, together with the papers of the Second Symposium on Artificial Intelligence and Neuroscience, ACAIN 2022. The total of 84 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 226 submissions. These research articles were written by leading scientists in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, neuroscience, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and applications.
Machine Learning, Optimization, and Data Science
This two-volume set, LNCS 13810 and 13811, constitutes the refereed proceedings of the 8th International Conference on Machine Learning, Optimization, and Data Science, LOD 2022, together with the papers of the Second Symposium on Artificial Intelligence and Neuroscience, ACAIN 2022. The total of 84 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 226 submissions. These research articles were written by leading scientists in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, neuroscience, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and applications.
Demystifying Big Data Analytics for Industries and Smart Societies
This book aims to provide readers with a comprehensive guide to the fundamentals of big data analytics and its applications in various industries and smart societies. What sets this book apart is its in-depth coverage of different aspects of big data analytics, including machine learning algorithms, spatial data analytics, and IoT-based smart systems for precision agriculture. The book also delves into the use of big data analytics in healthcare, energy management, and agricultural development, among others. The authors have used clear and concise language, along with relevant examples and case studies, to help readers understand the complex concepts involved in big data analytics.Key Features: Comprehensive coverage of the fundamentals of big data analytics In-depth discussion of different aspects of big data analytics, including machine learning algorithms, spatial data analytics, and IoT-based smart systems Practical examples and case studies to help readers understand complex concepts Coverage of the use of big data analytics in various industries, including healthcare, energy management, and agriculture Discussion of challenges and legal frameworks involved in big data analytics Clear and concise language that is easy to understand This book is a valuable resource for business owners, data analysts, students, and anyone interested in the field of big data analytics. It provides readers with the tools they need to leverage the power of big data and make informed decisions that can help their organizations succeed. Whether you are new to the field or an experienced practitioner, "Demystifying Big Data Analytics for Industries and Smart Societies" is must-read.
Machine Learning in Microservices
Implement real-world machine learning in a microservices architecture as well as design, build, and deploy intelligent microservices systems using examples and case studiesPurchase of the print or Kindle book includes a free PDF eBookKey Features: Design, build, and run microservices systems that utilize the full potential of machine learningDiscover the latest models and techniques for combining microservices and machine learning to create scalable systemsImplement machine learning in microservices architecture using open source applications with pros and consBook Description: With the rising need for agile development and very short time-to-market system deployments, incorporating machine learning algorithms into decoupled fine-grained microservices systems provides the perfect technology mix for modern systems. Machine Learning in Microservices is your essential guide to staying ahead of the curve in this ever-evolving world of technology.The book starts by introducing you to the concept of machine learning microservices architecture (MSA) and comparing MSA with service-based and event-driven architectures, along with how to transition into MSA. Next, you'll learn about the different approaches to building MSA and find out how to overcome common practical challenges faced in MSA design. As you advance, you'll get to grips with machine learning (ML) concepts and see how they can help better design and run MSA systems. Finally, the book will take you through practical examples and open source applications that will help you build and run highly efficient, agile microservices systems.By the end of this microservices book, you'll have a clear idea of different models of microservices architecture and machine learning and be able to combine both technologies to deliver a flexible and highly scalable enterprise system.What You Will Learn: Recognize the importance of MSA and ML and deploy both technologies in enterprise systemsExplore MSA enterprise systems and their general practical challengesDiscover how to design and develop microservices architectureUnderstand the different AI algorithms, types, and models and how they can be applied to MSAIdentify and overcome common MSA deployment challenges using AI and ML algorithmsExplore general open source and commercial tools commonly used in MSA enterprise systemsWho this book is for: This book is for machine learning solution architects, system and machine learning developers, and system and solution integrators of private and public sector organizations. Basic knowledge of DevOps, system architecture, and artificial intelligence (AI) systems is assumed, and working knowledge of the Python programming language is highly desired.
Managing Datasets and Models
This book contains a fast-paced introduction to data-related tasks in preparation for training models ondatasets. It presents a step-by-step, Python-based code sample that uses the kNN algorithm to manage a model on a dataset. Chapter One begins with an introduction to datasets and issues that can arise, followed by Chapter Two on outliers and anomaly detection. The next chapter explores ways for handling missing data and invalid data, and Chapter Four demonstrates how to train models with classification algorithms. Chapter 5 introduces visualization toolkits, such as Sweetviz, Skimpy, Matplotlib, and Seaborn, along with some simple Python-based code samples that render charts and graphs. An appendix includes some basics on using awk. Companion files with code, datasets, and figures are available for downloading.FEATURES: Covers extensive topics related to cleaning datasets and working with modelsIncludes Python-based code samples and a separate chapter on Matplotlib and SeabornFeatures companion files with source code, datasets, and figures from the book
Information Technology for Management: Approaches to Improving Business and Society
This book constitutes revised selected and extended papers presented at track 4 of the Conference on Computer Science and Intelligence Systems, FedCSIS 2022, which took place in Sofia, Bulgaria, during September 4-7, 2022.The FedCSIS Information Systems and Technologies Track included AIST 2022, ISM 2022, DSH 2022, and KAM 2022. AIST 2022 received 11 submissions, from which 2 full papers and 1 short paper have been accepted; for ISM 2022 2 full and 3 short papers have been accepted from 15 submissions; and for DSH 2022 2 full and 1 short papers have been accepted from 11 submissions. From the 17 submissions to KAM 2022, no paper passed the extended reviews, so the overall acceptance rate was 20% for full and 18% for short papers. The papers were organized in topical sections named: Approaches to improving business; approaches to improving society; and methods for improving business and society.
Robo-Advisor with Python
Build your own robo-advisor in Python to manage your investments and get up and running in no timePurchase of the print or Kindle book includes a free PDF eBookKey Features: Explore the use cases, workflow, and features that make up robo-advisorsLearn how to build core robo-advisor capabilities for goals, risk questions, portfolios, and projectionsDiscover how to operate the automated processes of a built and deployed robo-advisorBook Description: Robo-advisors are becoming table stakes for the wealth management industry across all segments, from retail to high-net-worth investors. Robo-advisors enable you to manage your own portfolios and financial institutions to create automated platforms for effective digital wealth management. This book is your hands-on guide to understanding how Robo-advisors work, and how to build one efficiently. The chapters are designed in a way to help you get a comprehensive grasp of what Robo-advisors do and how they are structured with an end-to-end workflow.You'll begin by learning about the key decisions that influence the building of a Robo-advisor, along with considerations on building and licensing a platform. As you advance, you'll find out how to build all the core capabilities of a Robo-advisor using Python, including goals, risk questionnaires, portfolios, and projections. The book also shows you how to create orders, as well as open accounts and perform KYC verification for transacting. Finally, you'll be able to implement capabilities such as performance reporting and rebalancing for operating a Robo-advisor with ease.By the end of this book, you'll have gained a solid understanding of how Robo-advisors work and be well on your way to building one for yourself or your business.What You Will Learn: Explore what Robo-advisors do and why they existCreate a workflow to design and build a Robo-advisor from the bottom upBuild and license Robo-advisors using different approachesOpen and fund accounts, complete KYC verification, and manage ordersBuild Robo-advisor features for goals, projections, portfolios, and moreOperate a Robo-advisor with P&L, rebalancing, and fee managementWho this book is for: If you are a finance professional or a data professional working in wealth management and are curious about how robo-advisors work, this book is for you. It will be helpful to have a basic understanding of Python and investing concepts. This is a great handbook for developers interested in building their own robo-advisor to manage personal investments or build a platform for their business to operate, as well as for product managers and business leaders in financial services looking to lease, buy, or build a robo-advisor.
Dynamics in Logic and Language
Edited in collaboration with FoLLI, the Association of Logic, Language and Information, this book constitutes the refereed proceedings of the Third Tsinghua Interdisciplinary Workshop on Logic, Language, and Meaning, TLLM 2022, which was held virtually in April 2022.The 9 full papers presented in this volume were carefully reviewed and selected from 13 submissions. The workshop covers a wide range of topics such as dynamic semantics, logical dynamics, Dynamic Epistemic Logic, Discourse Representation Theory, formal semantics, free choice inference, update semantics, and donkey sentences.
Rise of the Data Lakehouse
The data lakehouse is the next generation of the data warehouse and data lake, designed to meet today's complex and ever-changing analytics, machine learning, and data science requirements.Learn about the features and architecture of the data lakehouse, along with its powerful analytical infrastructure. Appreciate how the universal common connector blends structured, textual, analog, and IoT data. Maintain the lakehouse for future generations through Data Lakehouse Housekeeping and Data Future-proofing. Incorporate data catalogs, data lineage tools, and open source software into your architecture to ensure your data scientists, analysts, and end users live happily ever after. Deep dive into one specific implementation of a data lakehouse: the Databricks Lakehouse Platform.
Modern Oracle Database Programming
Level up your skill set to the latest that Oracle Database can offer. This book introduces features that are not well known that can transform your development efforts. You'll discover built-in functionality that can save you massive amounts of time that otherwise would be spent reinventing the wheel. You'll find that what used to take a lot of programming some years ago can be done with less code in a more reliable way today. Anyone using Oracle Database without the knowledge in this book is leaving valuable functionality-that their company has paid for-on the table, and this book opens the door to that functionality so that you can deliver reliable and performant solutions faster and more easily than ever.Part I looks at features in SQL and PL/SQL that are underused and not well known. You'll learn about new join types, pattern matching across rows, Top N pagination (useful in reporting!), qualified expressions, and enhancements to iterators that reduce code complexity and make your logic easier to understand.Part II covers how and when to invoke PL/SQL from SQL while maintaining performance. You'll learn about SQL macro functions for creating reusable SQL fragments, polymorphic table functions with return types determined by incoming argument types, and constructing and parsing JSON documents for data interchange with other systems.Part III introduces a vast array of built-in functionality that Oracle provides that is just waiting to be used. Edition-based redefinition enables zero-downtime application and schema upgrades. Data redaction enables easier compliance with privacy laws and similar regulations by protecting sensitive data from those who have no need to see it. Virtual private databases provide the appearance of giving each user their own database, again helping to secure sensitive data. These features are just a taste of what the book provides. Soon you'll be improving your skillsand wondering why you ever worked so hard to solve problems that Oracle Database already solves for you. What You Will LearnWrite more powerful code by incorporating underused features in SQL and PL/SQLOptimize your integration between SQL and PL/SQL for best performanceTake advantage of enhanced set operators, lateral joins, row-based pattern matching, and other advanced features in SQLMake your code easier to understand through your use of newer PL/SQL features, such as qualified expressions and iterator enhancementsIntegrate with web services and external data sources directly from the databaseCreate and parse JSON documents for easy data exchange and flexible schema design Who This Book Is ForAny developer who is writing SQL or PL/SQL, PL/SQL experts who want to level up their knowledgeand skills to the latest features that Oracle Database provides, and developers who don't want to write their own solutions only to find out later that they've wasted their time by building something that Oracle Database provides out of the box
Intelligent Robotics
This book constitutes selected papers presented during the Third China Annual Intelligent Robotics Conference, CCF CIRAC 2022, held in Xi' an, China, in December 2022. The 35 papers presented were thoroughly reviewed and selected from the 120 qualified submissions. They are organized in the following topical sections: robot safety; intelligent robot sensing; autonomous robot navigation; artificial intelligence and cloud robot; unmanned cluster collaboration; natural human-computer interaction; other robot-related technologies.
Learning Ray
Get started with Ray, the open source distributed computing framework that simplifies the process of scaling compute-intensive Python workloads. With this practical book, Python programmers, data engineers, and data scientists will learn how to leverage Ray locally and spin up compute clusters. You'll be able to use Ray to structure and run machine learning programs at scale. Authors Max Pumperla, Edward Oakes, and Richard Liaw show you how to build machine learning applications with Ray. You'll understand how Ray fits into the current landscape of machine learning tools and discover how Ray continues to integrate ever more tightly with these tools. Distributed computation is hard, but by using Ray you'll find it easy to get started. Learn how to build your first distributed applications with Ray Core Conduct hyperparameter optimization with Ray Tune Use the Ray RLlib library for reinforcement learning Manage distributed training with the Ray Train library Use Ray to perform data processing with Ray Datasets Learn how work with Ray Clusters and serve models with Ray Serve Build end-to-end machine learning applications with Ray AIR
Loss Data Analysis
This volume deals with two complementary topics. On one hand the book deals with the problem of determining the the probability distribution of a positive compound random variable, a problem which appears in the banking and insurance industries, in many areas of operational research and in reliability problems in the engineering sciences. On the other hand, the methodology proposed to solve such problems, which is based on an application of the maximum entropy method to invert the Laplace transform of the distributions, can be applied to many other problems. The book contains applications to a large variety of problems, including the problem of dependence of the sample data used to estimate empirically the Laplace transform of the random variable. ContentsIntroductionFrequency modelsIndividual severity modelsSome detailed examplesSome traditional approaches to the aggregation problemLaplace transforms and fractional moment problemsThe standard maximum entropy methodExtensions of the method of maximum entropySuperresolution in maxentropic Laplace transform inversionSample data dependenceDisentangling frequencies and decompounding lossesComputations using the maxentropic densityReview of statistical procedures
Computational Data and Social Networks
This book constitutes the refereed proceedings of the 11th International Conference on Computational Data and Social Networks, CSoNet 2022, held as a Virtual Event, during December 5-7, 2022. The 17 full papers and 7 short papers included in this book were carefully reviewed and selected from 47 submissions. They were organized in topical sections as follows: Machine Learning and Prediction, Security and Blockchain, Fact-checking, Fake News, and Hate Speech, Network Analysis, Optimization.
Transactions on Large-Scale Data- And Knowledge-Centered Systems LIII
The LNCS journal Transactions on Large-scale Data and Knowledge-centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing (e.g. computing resources, services, metadata, data sources) across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. This, the 53rd issue of Transactions on Large-scale Data and Knowledge-centered Systems, contains six fully revised selected regular papers. Topics covered include time series management from edge to cloud, segmentation for time series representation, similarity research, semantic similarity in a taxonomy, linked data semantic distance, linguistics-informed natural language processing, graph neural network, protected features, imbalanced data, causal consistency in distributed databases, actor model, and elastic horizontal scalability.
Digital Transformation
Digital Transformation in Industry 4.0/5.0 requires the effective and efficient application of digitalization technologies in the area of production systems. This book elaborates on concepts, techniques, and technologies from computer science in the context of Industry 4.0/5.0 and demonstrates their possible applications. Thus, the book serves as an orientation but also as a reference work for experts in the field of Industry 4.0/5.0 to successfully advance digitization in their companies.
Data Mining and Predictive Analytics for Business Decisions
With many recent advances in data science, we have many more tools and techniques available for data analysts to extract information from data sets. This book will assist data analysts to move up from simple tools such as Excel for descriptive analytics to answer more sophisticated questions using machine learning. Most of the exercises use R and Python, but rather than focus on coding algorithms, the book employs interactive interfaces to these tools to perform the analysis. Using the CRISP-DM data mining standard, the early chapters cover conducting the preparatory steps in data mining: translating business information needs into framed analytical questions and data preparation. The Jamovi and the JASP interfaces are used with R and the Orange3 data mining interface with Python. Where appropriate, Voyant and other open-source programs are used for text analytics. The techniques covered in this book range from basic descriptive statistics, such as summarization and tabulation, to more sophisticated predictivetechniques, such as linear and logistic regression, clustering, classification, and text analytics. Includes companion files with case study files, solution spreadsheets, data sets and charts, etc. from the book. FEATURES: Covers basic descriptive statistics, such as summarization and tabulation, to more sophisticated predictive techniques, such as linear and logistic regression, clustering, classification, and text analyticsUses R, Python, Jamovi and JASP interfaces, and the Orange3 data mining interfaceIncludes companion files with the case study files from the book, solution spreadsheets, data sets, etc.
Tableau Desktop Specialist Certification
Master Tableau fundamentals and get the one and only Tableau certification that never expires, while expediting your journey from zero to certificationKey Features: Learn how Tableau works inside and out for basic as well as intermediate uses of the applicationGain knowledge from a Tableau visionary and ambassador who successfully passed the examination in 2021Understand what is needed to pass a knowledge-based examination without having to use Tableau in the processBook Description: The Tableau Desktop Specialist certification is fundamental for any data visualization professional who works in the field with Tableau.This book gets you started by covering the exam format, Tableau basics, and best practices for preparing data for analysis and visualization. It also builds on your knowledge of advanced Tableau topics to get you up to speed with the essential domains and domain objectives. Although the guide provides an outline and starting point to key in on what needs to be understood before the examination, it also delivers in context to give you a strong understanding of each piece before taking the exam. Instructions on how to get hands on with examples, a common data source, and suggested elements are also included. Understanding the concepts will not only assist you in passing the examination, but will also help you work effectively with the tool in your workspace.By the end of this book, you'll be able to efficiently prepare for the certification exam with the help of mock tests, detailed explanations, and expert advice from the author.What You Will Learn: Understand how to add data to the applicationExplore data for insights in TableauDiscover what charts to use when visualizing for audiencesUnderstand functions, calculations and the basics of parametersWork with dimensions, measures and their variationsContextualize a visualization with marksShare insights and focus on editing a Tableau visualizationWho this book is for: If you're a data analyst, data scientist, or if you just want to enhance your data visualization tool stack, this book is for you. It's designed for those without prior and those with minimal exposure to Tableau, which also means it's useful for anyone moving into their first role that relies on data visualization.
Meta-Heuristic Algorithms for Advanced Distributed Systems
META-HEURISTIC ALGORITHMS FOR ADVANCED DISTRIBUTED SYSTEMS Discover a collection of meta-heuristic algorithms for distributed systems in different application domains Meta-heuristic techniques are increasingly gaining favor as tools for optimizing distributed systems--generally, to enhance the utility and precision of database searches. Carefully applied, they can increase system effectiveness, streamline operations, and reduce cost. Since many of these techniques are derived from nature, they offer considerable scope for research and development, with the result that this field is growing rapidly. Meta-Heuristic Algorithms for Advanced Distributed Systems offers an overview of these techniques and their applications in various distributed systems. With strategies based on both global and local searching, it covers a wide range of key topics related to meta-heuristic algorithms. Those interested in the latest developments in distributed systems will find this book indispensable. Meta-Heuristic Algorithms for Advanced Distributed Systems readers will also find: Analysis of security issues, distributed system design, stochastic optimization techniques, and more Detailed discussion of meta-heuristic techniques such as the genetic algorithm, particle swam optimization, and many others Applications of optimized distribution systems in healthcare and other key industries Meta-Heuristic Algorithms for Advanced Distributed Systems is ideal for academics and researchers studying distributed systems, their design, and their applications.
Process Mining Workshops
This open access book constitutes revised selected papers from the International Workshops held at the 4th International Conference on Process Mining, ICPM 2022, which took place in Bozen-Bolzano, Italy, during October 23-28, 2022. 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 42 papers included in this volume were carefully reviewed and selected from 89 submissions. They stem from the following workshops: - 3rd International Workshop on Event Data and Behavioral Analytics (EDBA)- 3rd International Workshop on Leveraging Machine Learning in Process Mining (ML4PM)- 3rd International Workshop on Responsible Process Mining (RPM) (previously known as Trust, Privacy and Security Aspects in Process Analytics)- 5th International Workshop on Process-Oriented Data Science for Healthcare (PODS4H)-3rd International Workshop on Streaming Analytics for Process Mining (SA4PM)- 7th International Workshop on Process Querying, Manipulation, and Intelligence (PQMI)- 1st International Workshop on Education meets Process Mining (EduPM)- 1st International Workshop on Data Quality and Transformation in Process Mining (DQT-PM)
Applied Geospatial Data Science with Python
Intelligently connect data points and gain a deeper understanding of environmental problems through hands-on Geospatial Data Science case studies written in PythonThe book includes colored images of important conceptsKey Features: Learn how to integrate spatial data and spatial thinking into traditional data science workflowsDevelop a spatial perspective and learn to avoid common pitfalls along the wayGain expertise through practical case studies applicable in a variety of industries with code samples that can be reproduced and expandedBook Description: Data scientists, when presented with a myriad of data, can often lose sight of how to present geospatial analyses in a meaningful way so that it makes sense to everyone. Using Python to visualize data helps stakeholders in less technical roles to understand the problem and seek solutions. The goal of this book is to help data scientists and GIS professionals learn and implement geospatial data science workflows using Python.Throughout this book, you'll uncover numerous geospatial Python libraries with which you can develop end-to-end spatial data science workflows. You'll learn how to read, process, and manipulate spatial data effectively. With data in hand, you'll move on to crafting spatial data visualizations to better understand and tell the story of your data through static and dynamic mapping applications. As you progress through the book, you'll find yourself developing geospatial AI and ML models focused on clustering, regression, and optimization. The use cases can be leveraged as building blocks for more advanced work in a variety of industries.By the end of the book, you'll be able to tackle random data, find meaningful correlations, and make geospatial data models.What You Will Learn: Understand the fundamentals needed to work with geospatial dataTransition from tabular to geo-enabled data in your workflowsDevelop an introductory portfolio of spatial data science work using PythonGain hands-on skills with case studies relevant to different industriesDiscover best practices focusing on geospatial data to bring a positive change in your environmentExplore solving use cases, such as traveling salesperson and vehicle routing problemsWho this book is for: This book is for you if you are a data scientist seeking to incorporate geospatial thinking into your workflows or a GIS professional seeking to incorporate data science methods into yours. You'll need to have a foundational knowledge of Python for data analysis and/or data science.
Intertwining Graphonomics with Human Movements
This book constitutes the proceedings of the 20th International Conference of the International Graphonomics Society, IGS 2021/2022. Originally planned to be celebrated in September 2021, due to the COVID-19 pandemic it was held in June 2022.The 36 full and 3 short papers presented at the conference were carefully reviewed and selected from 41 submissions and reviewed by a committee of 67 reviewers. Out of the 41 conferences, 26 papers were selected to be published in this proceedings. The program was comprised of 6 oral sessions on the following topics: historical documents, forensic handwriting examinations, handwriting learning and development, and motor control. One additional poster session included papers on all previous topics, and three special sessions included papers on neurodegenerative disorders.
Caie Igcse Ict Exam Success Guide and Website Link 3rd Edition
Learn Azure Synapse Data Explorer
A hands-on guide to working on use cases helping you ingest, analyze, and serve insightful data from IoT as well as telemetry data sources using Azure Synapse Data ExplorerFree PDF included with this bookKey Features: Augment advanced analytics projects with your IoT and application dataExpand your existing Azure Synapse environments with unstructured dataBuild industry-level projects on integration, experimentation, and dashboarding with Azure SynapseBook Description: Large volumes of data are generated daily from applications, websites, IoT devices, and other free-text, semi-structured data sources. Azure Synapse Data Explorer helps you collect, store, and analyze such data, and work with other analytical engines, such as Apache Spark, to develop advanced data science projects and maximize the value you extract from data.This book offers a comprehensive view of Azure Synapse Data Explorer, exploring not only the core scenarios of Data Explorer but also how it integrates within Azure Synapse. From data ingestion to data visualization and advanced analytics, you'll learn to take an end-to-end approach to maximize the value of unstructured data and drive powerful insights using data science capabilities. With real-world usage scenarios, you'll discover how to identify key projects where Azure Synapse Data Explorer can help you achieve your business goals. Throughout the chapters, you'll also find out how to manage big data as part of a software as a service (SaaS) platform, as well as tune, secure, and serve data to end users.By the end of this book, you'll have mastered the big data life cycle and you'll be able to implement advanced analytical scenarios from raw telemetry and log data.What You Will Learn: Integrate Data Explorer pools with all other Azure Synapse servicesCreate Data Explorer pools with Azure Synapse Studio and Azure PortalIngest, analyze, and serve data to users using Azure Synapse pipelinesIntegrate Power BI and visualize data with Synapse StudioConfigure Azure Machine Learning integration in Azure SynapseManage cost and troubleshoot Data Explorer pools in Synapse AnalyticsSecure Synapse workspaces and grant access to Data Explorer poolsWho this book is for: If you are a data engineer, data analyst, or business analyst working with unstructured data and looking to learn how to maximize the value of such data, this book is for you. If you already have experience working with Azure Synapse and want to incorporate unstructured data into your data science project, you'll also find plenty of useful information in this book. To maximize your learning experience, familiarity with data and performing simple queries using SQL or KQL is recommended. Basic knowledge of Python will help you get more from the examples.
Data Mining Models of Surface Inspection and Identification of Accurate Defects in Steel Sheet
Data mining models are used to analyze large amounts of data in order to identify patterns and relationships that can be used for decision making. In the context of surface inspection and identification of accurate defects in steel sheets, data mining models can be used to analyze images of the steel sheets and identify defects such as cracks, scratches, and other surface imperfections.One type of data mining model that can be used for this purpose is called a "convolutional neural network" (CNN). This type of model is able to analyze images and identify patterns within them, making it well-suited for identifying defects in steel sheet images.Another type of data mining model that can be used is called "Support Vector Machine" (SVM). It is an algorithm that can be used to classify the steel sheets into defective or non-defective based on the features extracted from the images of the steel sheets.Additionally, other data mining models like Random Forest, Decision Trees, K-Nearest Neighbors, and Naive Bayes can also be used to classify and identify the defects in steel sheets.Overall, data mining models can be an effective way to analyze images of steel sheets and identify defects. These models can be trained using large amounts of data and can be used to classify the steel sheets into defective or non-defective with high accuracy.Steel is one of the high demanded industrial material. It has a crucial role in increasing the per capita income of the country. It also acts as the primary material in many industries like construction, infrastructure, making pieces of machinery. Steel is the material found in common demand worldwide. Therefore, quality assurance of the material is considered as the most essential attribute. Due to increased competition in product supply makes, the manufacturer task to find a suitable market for his/her product challenging. However, an ever-ending requirement for the quality of industrial products in the market. Hence, it is becoming unavoidable to have an eye on the perfection of the product to meet up the international standards. This helps the steel industries to compete globally .Efficiency in steel production must be maximised, and inspection in the quality has to be enhanced. In the present scenario, the quality check is done visually by employing human resources. This process is time-consuming, and the efficiency of the work is not entirely reliable to meet the global standards. Hence it has laid a path to automate the defect detection and classify the defected products to reduce the defects in the finished products.Surface defects detection technique is widely applied in industrial scenarios. The surface quality inspection of steel plate has passed through three stages of development, including manual visual inspection, traditional non-destructive testing, and machine vision detection. Artificial visual inspection commonly uses the stroboscopic method.
Root Cause Analysis, Second Edition
This bestseller can help anyone whose role is to try to find specific causes for failures.It provides detailed steps for solving problems, focusing more heavily on the analytical process involved in finding the actual causes of problems. It does this using figures, diagrams, and tools useful for helping to make our thinking visible. This increases our ability to see what is truly significant and to better identify errors in our thinking. In the sections on finding root causes, this second edition now includes more examples on the use of multi-vari charts; how thought experiments can help guide data interpretation; how to enhance the value of the data collection process; cautions for analyzing data; and what to do if one can't find the causes. In its guidance on solution identification, biomimicry and TRIZ have been added as potential solution identification techniques. In addition, the appendices have been revised to include: an expanded breakdown of the 7 M's, which includes more than 50 specific possible causes; forms for tracking causes and solutions, which can help maintain alignment of actions; techniques for how to enhance the interview process; and example responses to problem situations that the reader can analyze for appropriateness.
Ubiquitous Security
This book constitutes the refereed proceedings of the Second International Conference, UbiSec 2022, held in Zhangjiajie, China, during December 28-31, 2022.The 34 full papers and 4 short papers included in this book were carefully reviewed and selected from 98 submissions. They were organized in topical sections as follows: cyberspace security, cyberspace privacy, cyberspace anonymity and short papers.
Artificial Intelligence
This three-volume set LNCS 13604-13606 constitutes revised selected papers presented at the Second CAAI International Conference on Artificial Intelligence, held in Beijing, China, in August 2022. CICAI is a summit forum in the field of artificial intelligence and the 2022 forum was hosted by Chinese Association for Artificial Intelligence (CAAI). The 164 papers were thoroughly reviewed and selected from 521 submissions. CICAI aims to establish a global platform for international academic exchange, promote advanced research in AI and its affiliated disciplines such as machine learning, computer vision, natural language, processing, and data mining, amongst others.
Electronic Governance with Emerging Technologies
This book constitutes selected and revised papers presented at the First International Conference on Electronic Governance with Emerging Technologies, EGETC 2022, held in Tampico, Mexico, in September 2022. The 15 full papers and 2 short papers presented were thoroughly reviewed and selected from the 54 submissions. This volume focuses on the recent developmentsin the domain of eGovernment and governance of digital organizations also aims to shed light on the emerging research trends and their applications.
Mathematical Foundations of Software Engineering
This textbook presents an introduction to the mathematical foundations of software engineering. It presents the rich applications of mathematics in areas such as error-correcting codes, cryptography, the safety and security critical fields, the banking and insurance fields, as well as traditional engineering applications. Topics and features: Addresses core mathematics for critical thinking and problem solving Discusses propositional and predicate logic and various proof techniques to demonstrate the correctness of a logical argument. Examines number theory and its applications to cryptography Considers the underlying mathematics of error-correcting codes Discusses graph theory and its applications to modelling networks Reviews tools to support software engineering mathematics, including automated and interactive theorem provers and model checkingDiscusses financial software engineering, including simple and compound interest, probability and statistics, and operations research Discusses software reliability and dependability and explains formal methods used to derive a program from its specification Discusses calculus, matrices, vectors, complex numbers, and quaternions, as well as applications to graphics and robotics Includes key learning topics, summaries, and review questions in each chapter, together with a useful glossary This practical and easy-to-follow textbook/reference is ideal for computer science students seeking to learn how mathematics can assist them in building high-quality and reliable software on time and on budget. The text also serves as an excellent self-study primer for software engineers, quality professionals, and software managers.
Julia for Data Analysis
Master core data analysis skills using Julia. Interesting hands-on projects guide you through time series data, predictive models, popularity ranking, and more. In Julia for Data Analysis you will learn how to: Read and write data in various formats Work with tabular data, including subsetting, grouping, and transforming Visualize your data Build predictive models Create data processing pipelines Create web services sharing results of data analysis Write readable and efficient Julia programs Julia was designed for the unique needs of data scientists: it's expressive and easy-to-use whilst also delivering super-fast code execution. Julia for Data Analysis shows you how to take full advantage of this amazing language to read, write, transform, analyze, and visualize data--everything you need for an effective data pipeline. It's written by Bogumil Kaminski, one of the top contributors to Julia, #1 Julia answerer on StackOverflow, and a lead developer of Julia's core data package DataFrames.jl. Its engaging hands-on projects get you into the action quickly. Plus, you'll even be able to turn your new Julia skills to general purpose programming! Foreword by Viral Shah. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Julia is a great language for data analysis. It's easy to learn, fast, and it works well for everything from one-off calculations to full-on data processing pipelines. Whether you're looking for a better way to crunch everyday business data or you're just starting your data science journey, learning Julia will give you a valuable skill. About the book Julia for Data Analysis teaches you how to handle core data analysis tasks with the Julia programming language. You'll start by reviewing language fundamentals as you practice techniques for data transformation, visualizations, and more. Then, you'll master essential data analysis skills through engaging examples like examining currency exchange, interpreting time series data, and even exploring chess puzzles. Along the way, you'll learn to easily transfer existing data pipelines to Julia. What's inside Read and write data in various formats Work with tabular data, including subsetting, grouping, and transforming Create data processing pipelines Create web services sharing results of data analysis Write readable and efficient Julia programs About the reader For data scientists familiar with Python or R. No experience with Julia required. About the author Bogumil Kaminski iis one of the lead developers of DataFrames.jl--the core package for data manipulation in the Julia ecosystem. He has over 20 years of experience delivering data science projects. Table of Contents 1 Introduction PART 1 ESSENTIAL JULIA SKILLS 2 Getting started with Julia 3 Julia's support for scaling projects 4 Working with collections in Julia 5 Advanced topics on handling collections 6 Working with strings 7 Handling time-series data and missing values PART 2 TOOLBOX FOR DATA ANALYSIS 8 First steps with data frames 9 Getting data from a data frame 10 Creating data frame objects 11 Converting and grouping data frames 12 Mutating and transforming data frames 13 Advanced transformations of data frames 14 Creating web services for sharing data analysis results
Data Analytics Initiatives
The categorisation of analytical projects could help to simplify complexity reasonably and, at the same time, clarify the critical aspects of analytical initiatives. But how can this complex work be categorized? What makes it so complex?Data Analytics Initiatives: Managing Analytics for Success emphasizes that each analytics project is different. At the same time, analytics projects have many common aspects, and these features make them unique compared to other projects. Describing these commonalities helps to develop a conceptual understanding of analytical work. However, features specific to each initiative affects the entire analytics project lifecycle. Neglecting them by trying to use general approaches without tailoring them to each project can lead to failure.In addition to examining typical characteristics of the analytics project and how to categorise them, the book looks at specific types of projects, provides a high-level assessment of their characteristics from a risk perspective, and comments on the most common problems or challenges. The book also presents examples of questions that could be asked of relevant people to analyse an analytics project. These questions help to position properly the project and to find commonalities and general project challenges.
Solution Architecture Patterns for Enterprise
Gain a deeper understanding of how distributed systems work, as well as which applications and systems are used for specific business domains or industries. This book provides a set of solution architecture patterns that were developed based on the author's experience building enterprise software systems for hundreds of different organizations across the globe. The architecture diagrams (patterns) and examples allow you to not only grasp the concepts, but to build working projects. Solution Architecture Patterns for Enterprise starts with an introduction to the concepts of enterprise software systems and solution architecture and later moves to individual solution architecture patterns used in real-world enterprises. Subsequent sections cover various industry-specific solution architecture patterns that can be used to build domain-specific software systems. The book concludes with a view of what the future holds for solution architecture, including likely newdevelopments in the field. This book will help enterprise software architects and engineers to design and implement real-world enterprise software systems using best practices and techniques adopted by organizations across the globe. It provides software architecture blueprints to build domain-specific enterprise software systems. If you are working on any digital transformation project or initiative, you will find this book useful, as it provides quick reference on architecture and implementation to get started with your work. What You Will LearnUnderstand the key elements of enterprise software systems and how to design and implement themMaster different approaches to build real-world software applicationsBuild domain specific enterprise software systemsUse open-source tools to build enterprise software systems Who This Book Is For Software Developers, software architect, solution architects, and enterprise architects.
Computational Intelligence in Data Science
This book constitutes the refereed post-conference proceedings of the Fourth IFIP TC 12 International Conference on Computational Intelligence in Data Science, ICCIDS 2021, held in Chennai, India, in March 2021. The 20 revised full papers presented were carefully reviewed and selected from 75 submissions. The papers cover topics such as computational intelligence for text analysis; computational intelligence for image and video analysis; blockchain and data science.
Internet of Everything
This book constitutes the refereed post-conference proceedings of the EAI International Conference on Internet of Everything, IoECon 2022, which took place in Guimar瓊es, Portugal in September 16-17 2022. IoECon 2022 presents IoE paradigms to their whole dimension, intelligently connecting devices, people, processes, data, and things. IoE is multi-disciplinary and offers an opportunity to explore the co-relations between different areas, techniques, and theories about a new cyber world.The 10 revised full papers were carefully reviewed and selected from 26 submissions. The papers focus on a complete ecosystem that digitally interconnects everything, including people-to-people, people-to-machines, and machines-to-machines.
Web and Big Data
This three-volume set, LNCS 13421, 13422 and 13423, constitutes the thoroughly refereed proceedings of the 6th International Joint Conference, APWeb-WAIM 2022, held in Nanjing, China, in August 2022.The 75 full papers presented together with 45 short papers, and 5 demonstration papers were carefully reviewed and selected from 297 submissions. The papers are organized around the following topics: Big Data Analytic and Management, Advanced database and web applications, Cloud Computing and Crowdsourcing, Data Mining, Graph Data and Social Networks, Information Extraction and Retrieval, Knowledge Graph, Machine Learning, Query processing and optimization, Recommender Systems, Security, privacy, and trust and Blockchain data management and applications, and Spatial and multi-media data.
Concrete Abstractions
This book demonstrates how to formally model various mathematical domains (including algorithms operating in these domains) in a way that makes them amenable to a fully automatic analysis by computer software.The presented domains are typically investigated in discrete mathematics, logic, algebra, and computer science; they are modeled in a formal language based on first-order logic which is sufficiently rich to express the core entities in whose correctness we are interested: mathematical theorems and algorithmic specifications. This formal language is the language of RISCAL, a "mathematical model checker" by which the validity of all formulas and the correctness of all algorithms can be automatically decided. The RISCAL software is freely available; all formal contents presented in the book are given in the form of specification files by which the reader may interact with the software while studying the corresponding book material.
Everyday Enterprise Architecture
Discover what needs to happen in enterprise-architecture practice--and not just its outcomes, but also the activities from which those outcomes would arise. This book reveals how business and enterprise architects can deliver fast solutions to an always-on-the-go business world.To begin, you'll review a new technique called "context-space mapping," which provides a structured method for sense-making across the entire context of an enterprise. Throughout the book, you'll concentrate on the routine practices that underpin each of the architecture disciplines. Working step-by-step through a real 10-day architecture project, this book explores the activities that underpin the strategy, structures and solutions in the real-time turmoil of an enterprise architect's everyday work. You'll explore how and why and when the various documents, artefacts and items of 'theory-stuff' come into the practice - all those mainstream methods, frameworks, models, metamodels and other information sources. In the end, Everyday Enterprise Architecture will help you develop the skills, judgment, and awareness to keep enhancing the value of your architectural projects. What You'll LearnWork on architectures at "business-speed"Adapt architectures for different tasksGather, use, and manage architectural informationWho This Book Is ForEnterprise and business architects.
Expert Performance Indexing in Azure SQL and SQL Server 2022
Take a deep dive into perhaps the single most important facet of query performance--indexes--and how to best use them. Newly updated for SQL Server 2022 and Azure SQL, this fourth edition includes new guidance and features related to columnstore indexes, improved and consolidated content on Query Store, deeper content around Intelligent Query Processing, and other updates to help you optimize query execution and make performance improvements to even the most challenging workloads. The book begins with explanations of the types of indexes and how they are stored in a database. Moving further into the book, you will learn how statistics are critical for optimal index usage and how the Index Advisor can assist in reviewing and optimizing index health. This book helps you build a clear understanding of how indexes work, how to implement and use them, and the many options available to tame even the most large and complex workloads.What You Will LearnProperly index row store, columnstore, and memory-optimized tablesMake use of Intelligent Query Processing for faster query resultsReview statistics to understand indexing choices made by the optimizerApply indexing strategies such as covering indexes, included columns, and index intersectionsRecognize and remove unnecessary indexesDesign effective indexes for full-text, spatial, and XML data typesWho This Book Is ForAzure SQL and SQL Server administrators and developers who are ready to improve the performance of their database environment by thoughtfully building indexes to speed up queries that matter the most and make a difference to the business
MySQL Database Service Revealed
Access all the information you need to begin using the MySQL Database Service (MDS) in the Oracle Cloud Infrastructure (OCI). MDS is Oracle's new platform as a service (PAAS) offering for open-source database users. This book covers getting started with an account in OCI, gives a brief overview of OCI services available, and provides a short tutorial on MDS. Reading this book helps you take advantage of the powerful OCI features by building your own MySQL database in the cloud. Examples in this book center around running MDS in OCI, and include several of the popular use cases as well as advice on how to implement them. In addition, you will learn more about the related MDS OCI features, such as the high availability features currently available. Finally, you will learn how to back up and restore your data as well as how to get your data into and out of the cloud. The skills you learn in this book will help you get started using MDS and letting Oracle do the heavy lifting of managing MDS operations and implementation. What You Will LearnUse Oracle Cloud Infrastructure (OCI)Deploy MySQL Database Service (MDS) systems in the cloudConnect your applications to MDSBack up and recover using the data recovery features of MDSEmploy the newest high availability features of MDS Who This Book Is ForSystems engineers, developers, and database professionals who want to learn about the powerful features of the MySQL Database Service (MDS) and how to incorporate cloud-based database storage into their infrastructure and applications. Readers who are new to MySQL will appreciate the tutorial chapter, and those familiar with MySQL will learn the latest features of MDS as well as how to build inexpensive, powerful MySQL database servers in the Oracle Cloud Infrastructure (OCI).
Big Data - Bigdata 2022
This book constitutes the proceedings of the 11th International Conference on Big Data, BigData 2022, held as part of the Services Conference Federation, SCF 2022, held in Honolulu, HI, USA, in December 2022. The 4 full papers and 5 short papers presented in this volume were carefully reviewed and selected from 16 submissions. The 2022 International Congress on Big Data (BigData 2022) aims to provide an international forum that formally explores various business insights of all kinds of value-added "services". Big Data is a key enabler of exploring business insights and economics of services.
