- Table View
- List View
Active Machine Learning with Python: Refine and elevate data quality over quantity with active learning
by Margaux Masson-ForsytheUse active machine learning with Python to improve the accuracy of predictive models, streamline the data analysis process, and adapt to evolving data trends, fostering innovation and progress across diverse fieldsKey FeaturesLearn how to implement a pipeline for optimal model creation from large datasets and at lower costsGain profound insights within your data while achieving greater efficiency and speedApply your knowledge to real-world use cases and solve complex ML problemsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionBuilding accurate machine learning models requires quality data—lots of it. However, for most teams, assembling massive datasets is time-consuming, expensive, or downright impossible. Led by Margaux Masson-Forsythe, a seasoned ML engineer and advocate for surgical data science and climate AI advancements, this hands-on guide to active machine learning demonstrates how to train robust models with just a fraction of the data using Python's powerful active learning tools. You’ll master the fundamental techniques of active learning, such as membership query synthesis, stream-based sampling, and pool-based sampling and gain insights for designing and implementing active learning algorithms with query strategy and Human-in-the-Loop frameworks. Exploring various active machine learning techniques, you’ll learn how to enhance the performance of computer vision models like image classification, object detection, and semantic segmentation and delve into a machine AL method for selecting the most informative frames for labeling large videos, addressing duplicated data. You’ll also assess the effectiveness and efficiency of active machine learning systems through performance evaluation. By the end of the book, you’ll be able to enhance your active learning projects by leveraging Python libraries, frameworks, and commonly used tools.What you will learnMaster the fundamentals of active machine learningUnderstand query strategies for optimal model training with minimal dataTackle class imbalance, concept drift, and other data challengesEvaluate and analyze active learning model performanceIntegrate active learning libraries into workflows effectivelyOptimize workflows for human labelersExplore the finest active learning tools available todayWho this book is forIdeal for data scientists and ML engineers aiming to maximize model performance while minimizing costly data labeling, this book is your guide to optimizing ML workflows and prioritizing quality over quantity. Whether you’re a technical practitioner or team lead, you’ll benefit from the proven methods presented in this book to slash data requirements and iterate faster. Basic Python proficiency and familiarity with machine learning concepts such as datasets and convolutional neural networks is all you need to get started.
Microsoft Dynamics 365 AI for Business Insights: Transform your business processes with the practical implementation of Dynamics 365 AI modules
by Dmitry ShargorodskyStreamline your business operations by leveraging AI across key functions using practical examples and insightful case studiesKey FeaturesUncover the practical applications of Dynamics 365 AI across sales, customer service, marketing, and financeExplore Dynamics 365’s integration with advanced AI tools such as OpenAI, Azure Open AI, and MS CopilotLearn from real-world examples and case studiesPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionIf there is one hot topic being discussed in every boardroom meeting today, it’s AI. With Microsoft Dynamics 365 AI proving to be a game-changer, it’s essential for business professionals to master this tool. Microsoft Dynamics 365 AI for Business Insights will help you harness AI across key business functions to streamline processes and enhance customer experiences. Written by a seasoned professional with 15+ years of experience, this book guides you through Dynamics 365 AI’s practical applications across sales, customer service, marketing, and finance departments. You'll learn how to enhance customer experiences, streamline sales processes, optimize marketing strategies, and improve financial forecasting. This book also explores the integration of generative AI tools such as OpenAI Service, Azure Open AI, language models, and Microsoft Copilot within the Dynamics 365 ecosystem. With real-world examples, case studies, and expert insights, you’ll discover the transformative potential of this powerful toolkit. As well as driving sales insights and implementing fraud protection, you’ll explore emerging AI trends, Microsoft's roadmap for Dynamics 365 AI, and the upcoming features. By the end, you’ll be all set to unlock new growth opportunities using Dynamics 365 AI.What you will learnOvercome common challenges in Dynamics 365 AI implementation with easeDelve into the practical applications of advanced generative AI toolsIntegrate cutting-edge tools such as OpenAI Service, Azure Open AI, language models, and Microsoft Copilot with Dynamics 365 AIDerive insights from real-world examples of successful AI implementationDiscover best practices and strategies for leveraging AI to find useful business insights and enhance operationsExplore Microsoft's roadmap for Dynamics 365 AI and the forthcoming trends in AI for businessWho this book is forThis book is for Dynamics 365 consultants, architects, and IT managers, willing to implement AI in their organizations. Business consultants advising on business technology, especially those focused on Microsoft Dynamics 365, will find it useful for enhancing their skills. A basic understanding of Microsoft Dynamics 365 and its suite of business applications will be beneficial as the book’s focus is on implementing the tool’s AI modules. Familiarity with the principles of artificial intelligence and how it is applied in a business context will also be helpful.
The Definitive Guide to Data Integration: Unlock the power of data integration to efficiently manage, transform, and analyze data
by Pierre-Yves BONNEFOY Emeric CHAIZE Raphaël MANSUY Mehdi TAZILearn the essentials of data integration with this comprehensive guide, covering everything from sources to solutions, and discover the key to making the most of your data stackKey FeaturesLearn how to leverage modern data stack tools and technologies for effective data integrationDesign and implement data integration solutions with practical advice and best practicesFocus on modern technologies such as cloud-based architectures, real-time data processing, and open-source tools and technologiesPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionThe Definitive Guide to Data Integration is an indispensable resource for navigating the complexities of modern data integration. Focusing on the latest tools, techniques, and best practices, this guide helps you master data integration and unleash the full potential of your data. This comprehensive guide begins by examining the challenges and key concepts of data integration, such as managing huge volumes of data and dealing with the different data types. You’ll gain a deep understanding of the modern data stack and its architecture, as well as the pivotal role of open-source technologies in shaping the data landscape. Delving into the layers of the modern data stack, you’ll cover data sources, types, storage, integration techniques, transformation, and processing. The book also offers insights into data exposition and APIs, ingestion and storage strategies, data preparation and analysis, workflow management, monitoring, data quality, and governance. Packed with practical use cases, real-world examples, and a glimpse into the future of data integration, The Definitive Guide to Data Integration is an essential resource for data eclectics. By the end of this book, you’ll have the gained the knowledge and skills needed to optimize your data usage and excel in the ever-evolving world of data.What you will learnDiscover the evolving architecture and technologies shaping data integrationProcess large data volumes efficiently with data warehousingTackle the complexities of integrating large datasets from diverse sourcesHarness the power of data warehousing for efficient data storage and processingDesign and optimize effective data integration solutionsExplore data governance principles and compliance requirementsWho this book is forThis book is perfect for data engineers, data architects, data analysts, and IT professionals looking to gain a comprehensive understanding of data integration in the modern era. Whether you’re a beginner or an experienced professional enhancing your knowledge of the modern data stack, this definitive guide will help you navigate the data integration landscape.
Mastering Microsoft Intune: Deploy Windows 11, Windows 365 via Microsoft Intune, Copilot and advance management via Intune Suite
by Christiaan Brinkhoff Per LarsenGet ready to master Microsoft Intune and revolutionize your endpoint management strategy with this comprehensive guide and provide next-level security with the Intune Suite. Includes forewords from Scott Manchester, Vice President, Windows 365 + AVD and Steve Dispensa Corporate Vice President, Microsoft Intune.Key FeaturesThis new edition covers the latest updates of Microsoft Intune, Windows 365, Intune Suite, Windows Autopatch, Microsoft Defender and Universal PrintGet detailed guidance on device enrolment, app deployment, management, data security, and policy configurationSecure data on personal devices with app policies, encryption, and moreBook DescriptionThe slow adoption of modern Work solutions, which are designed to streamline the management of your environment, can often be attributed to a lack of understanding and familiarity with those solutions. This book will provide you with all the information you need to successfully transition to Microsoft Intune. Mastering Microsoft Intune, Second Edition, explains various concepts in detail to give you the clarity on how to use Microsoft Intune and eliminate any migration challenges. You'll master Cloud Computing services such as Windows 365 Cloud PCs, Intune Suite, Windows Autopatch, Windows Autopilot, profile management, monitoring and analytics, Universal Print, and much more. The book will take you through the latest features and new Microsoft Cloud services to help you to get grips with the fundamentals of Intune and understand which services you can manage. Whether you're interested in physical or cloud endpoints it's all covered. By the end of the book, you'll be able to set up Intune and use it to run Windows and Windows 365 efficiently, using all the latest features of Intune.What you will learnSimplify the deployment of Windows in the cloud with Windows 365 Cloud PCsDeliver next-generation security features with Intune SuiteSimplify Windows Updates with Windows AutopatchConfigure advanced policy management within IntuneDiscover modern profile management and migration options for physical and Cloud PCsHarden security with baseline settings and other security best practicesFind troubleshooting tips and tricks for Intune, Windows 365 Cloud PCs, and moreDiscover deployment best practices for physical and cloud-managed endpointsWho this book is forIf you're an IT professional, enterprise mobility administrator, architect, or consultant looking to learn about managing Windows on both physical and cloud endpoints using Microsoft Intune, then this book is for you.
Technical Writing for Software Developers: Enhance communication, improve collaboration, and leverage AI tools for software development
by Chris ChinchillaElevate your software development process with expert technical writing skills, fostering clarity, collaboration, and successful product outcomesKey FeaturesOptimize documentation workflows with collaborative version-controlled "docs-as-code" tooling optionsEngage with interactive learning modules embedded throughout the bookImprove software quality as a lead developer through effective communication in documentationPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionEffective documentation is key to the success of products in remote software development teams, facilitating clear instructions that benefit the entire development team. Technical Writing for Software Developers lays a solid foundation of essential grammar, providing language tips and explaining how precise writing enhances documentation, and walks you through the fundamental types and styles of documentation. Starting with an exploration of the current state of the tech writing industry and its significance in both the software and hardware realms, you’ll master the building blocks of technical writing, exploring tooling choices and style guides, and create dynamic multimedia-laden documentation. This book equips you with valuable insights into the writing and feedback process to ensure continuous improvement. Additionally, you’ll take a peek at the emerging trends and technologies, including AI tools, shaping the future of technical writing. By the end of this technical writing book, you’ll have developed the expertise you need to tackle documentation requests effectively, armed with the knowledge of the best approach for documenting any topic, encompassing text, media elements, structure, and appropriate tools. The skills acquired will enable you to achieve seamless teamwork, enhanced project efficiency, and successful software development.What you will learnCreate engaging multimedia-rich documentationUnderstand the types and styles of documentationDiscover grammar and language tips for clear communicationStreamline your documentation process with the right tooling choiceMaster the writing and feedback process for continuous improvementExplore automation techniques for efficient documentation workflowsEmbrace AI-powered tools for enhanced technical writingWho this book is forThis book is for software developers who want to improve their technical writing prowess. Whether you are a junior developer looking to refine your documentation skills or a professional striving for smoother collaboration, this resource equips you with all the essential knowledge and practical insights you need. Covering everything from creating clear documentation to enhancing career prospects, this book caters to a diverse range of software developers, including programmers, software architects, and software engineers looking to streamline the product development process and save time.
Deep Learning for Time Series Cookbook: Use PyTorch and Python recipes for forecasting, classification, and anomaly detection
by Vitor Cerqueira Luís RoqueLearn how to deal with time series data and how to model it using deep learning and take your skills to the next level by mastering PyTorch using different Python recipesKey FeaturesLearn the fundamentals of time series analysis and how to model time series data using deep learningExplore the world of deep learning with PyTorch and build advanced deep neural networksGain expertise in tackling time series problems, from forecasting future trends to classifying patterns and anomaly detectionPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionMost organizations exhibit a time-dependent structure in their processes, including fields such as finance. By leveraging time series analysis and forecasting, these organizations can make informed decisions and optimize their performance. Accurate forecasts help reduce uncertainty and enable better planning of operations. Unlike traditional approaches to forecasting, deep learning can process large amounts of data and help derive complex patterns. Despite its increasing relevance, getting the most out of deep learning requires significant technical expertise. This book guides you through applying deep learning to time series data with the help of easy-to-follow code recipes. You’ll cover time series problems, such as forecasting, anomaly detection, and classification. This deep learning book will also show you how to solve these problems using different deep neural network architectures, including convolutional neural networks (CNNs) or transformers. As you progress, you’ll use PyTorch, a popular deep learning framework based on Python to build production-ready prediction solutions. By the end of this book, you'll have learned how to solve different time series tasks with deep learning using the PyTorch ecosystem.What you will learnGrasp the core of time series analysis and unleash its power using PythonUnderstand PyTorch and how to use it to build deep learning modelsDiscover how to transform a time series for training transformersUnderstand how to deal with various time series characteristicsTackle forecasting problems, involving univariate or multivariate dataMaster time series classification with residual and convolutional neural networksGet up to speed with solving time series anomaly detection problems using autoencoders and generative adversarial networks (GANs)Who this book is forIf you’re a machine learning enthusiast or someone who wants to learn more about building forecasting applications using deep learning, this book is for you. Basic knowledge of Python programming and machine learning is required to get the most out of this book.
Mastering Microsoft Dynamics 365 Business Central: The complete guide for designing and integrating advanced Business Central solutions
by Stefano Demiliani Duilio TacconiUtilize Microsoft Dynamics 365 Business Central's most recent capabilities to create bespoke business management solutions using best practices learned along the way from veterans in the industry. Purchase of the print or Kindle book includes a free PDF eBookKey FeaturesExtend Business Central's functionalities through Azure, Power Platform, GitHub, and custom extensionsUnlock the potential of data exchange and functionality expansion by integrating with external systems using APIs and ODataBuild reliable, maintainable, and continuously improving solutions while writing performant, well-structured code and using telemetries and DevOpsBook DescriptionThis book dives straight into guiding you through the process of building real-world solutions with the AL language and Visual Studio Code. It emphasizes best practices and extensibility patterns to ensure your extensions are well-structured, maintainable, and meet the needs of modern businesses. You'll learn advanced AL techniques, report creation methods, debugging strategies, and how to leverage telemetries for monitoring. Additionally, it covers performance optimization practices and API integration to help you create efficient and interconnected solutions. With a focus on extension development, this new edition allows you to jump right into coding without spending time on setup processes. This book introduces new chapters covering essential tasks that Business Central developers frequently encounter, such as file handling and printing management. Finally, the book expands its scope by including chapters on various integration aspects, including VS Code extensions, GitHub DevOps, Azure services, and Power Platform integrations. We’ll wrap up by covering Copilot capabilities in Business Central and how you can create your own generative AI copilots. By mastering these concepts and techniques, you'll be well-equipped to create powerful and customized solutions that extend the capabilities of Dynamics 365 Business Central.What you will learnDeveloping a customized solution for Dynamics 365 Business CentralWriting performant code following extensibility patternsHandling reporting, files, and printing on a cloud environmentHandling Business Central telemetries with AzureWriting APIs and integrations for Dynamics 365 Business CentralApplying DevOps and CI/CD to development projects by using GitHubIntegrating Business Central with Power PlatformPublishing your solutions to AppSource marketplaceManage Copilot capabilities and create your own generative AI copilotWho this book is forThis book is intended for new developers who want to get started with Dynamics 365 Business Central. Professionals with expertise will also benefit from this book by enhancing their knowledge and comprehension of Dynamics 365 Business Central development platform and best practices
C# Interview Guide: Boost your confidence with answers to hundreds of secret interview questions
by Konstantin SemenenkoCatapult your C# journey with this guide to crafting standout resumes, mastering advanced concepts, and navigating job offers with real-world insights for unparalleled success in programming and interviewsKey FeaturesAcquire a strong foundation in syntax, data types, and object-oriented programming to code confidentlyDevelop strategies for addressing behavioral questions, tackle technical challenges, and showcase your coding skillsAugment your C# programming skills with valuable insights from industry expertsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionIf you're gearing up for technical interviews by enhancing your programming skills and aiming for a successful career in C# programming and software development, the C# Interview Guide is your key to interview success. Designed to equip you with essential skills for excelling in technical interviews, this guide spans a broad spectrum, covering fundamental C# programming concepts to intricate technical details. As you progress, you'll develop proficiency in crafting compelling resumes, adeptly answering behavioral questions, and navigating the complexities of salary negotiations and job evaluations. What sets this book apart is its coverage, extending beyond technical know-how and incorporating real-world experiences and expert insights from industry professionals. This comprehensive approach, coupled with guidance on overcoming challenges, ranging from interview preparation to post-interview strategies, makes this guide an invaluable resource for those aspiring to advance in their C# programming careers. By the end of this guide, you’ll emerge with a solid understanding of C# programming, advanced technical interview skills, and the ability to apply industry best practices.What you will learnCraft compelling resumes and cover letters for impactful job applicationsDemonstrate proficiency in fundamental C# programming concepts and syntaxMaster advanced C# topics, including LINQ, asynchronous programming, and design patternsImplement best practices for writing clean, maintainable C# codeUse popular C# development tools and frameworks, such as .NET and .NET CoreNegotiate salary, evaluate job offers, and build a strong C# portfolioApply soft skills for successful interactions in C# development rolesWho this book is forThis book is for individuals aspiring to pursue a career in C# programming or software development. Whether you are a beginner or experienced professional, this guide will enhance your technical interview skills and C# programming knowledge.
Extending Power BI with Python and R: Perform advanced analysis using the power of analytical languages
by Luca ZavarellaIngest, transform, manipulate, and visualize your data beyond Power BI's capabilities. Purchase of the print or Kindle book includes a free eBook in PDF format.Key FeaturesDiscover best practices for using Python and R in Power BI by implementing non-trivial codeEnrich your Power BI dashboards using external APIs and machine learning modelsCreate any visualization, as complex as you want, using Python and R scriptsBook DescriptionThe latest edition of this book delves deep into advanced analytics, focusing on enhancing Python and R proficiency within Power BI. New chapters cover optimizing Python and R settings, utilizing Intel's Math Kernel Library (MKL) for performance boosts, and addressing integration challenges. Techniques for managing large datasets beyond available RAM, employing the Parquet data format, and advanced fuzzy matching algorithms are explored. Additionally, it discusses leveraging SQL Server Language Extensions to overcome traditional Python and R limitations in Power BI. It also helps in crafting sophisticated visualizations using the Grammar of Graphics in both R and Python. This Power BI book will help you master data validation with regular expressions, import data from diverse sources, and apply advanced algorithms for transformation. You'll learn how to safeguard personal data in Power BI with techniques like pseudonymization, anonymization, and data masking. You'll also get to grips with the key statistical features of datasets by plotting multiple visual graphs in the process of building a machine learning model. The book will guide you on utilizing external APIs for enrichment, enhancing I/O performance, and leveraging Python and R for analysis. You'll reinforce your learning with questions at the end of each chapter.What you will learnConfigure optimal integration of Python and R with Power BIPerform complex data manipulations not possible by default in Power BIBoost Power BI logging and loading large datasetsExtract insights from your data using algorithms like linear optimizationCalculate string distances and learn how to use them for probabilistic fuzzy matchingHandle outliers and missing values for multivariate and time-series dataApply Exploratory Data Analysis in Power BI with RLearn to use Grammar of Graphics in PythonWho this book is forThis book is for business analysts, business intelligence professionals, and data scientists who already use Microsoft Power BI and want to add more value to their analysis using Python and R. Working knowledge of Power BI is required to make the most of this book. Basic knowledge of Python and R will also be helpful.
Security-Driven Software Development: Learn to analyze and mitigate risks in your software projects
by Aspen OlmstedTrace security requirements through each development phase, mitigating multiple-layer attacks with practical examples, and emerge equipped with the skills to build resilient applicationsKey FeaturesExplore the practical application of secure software development methodologiesModel security vulnerabilities throughout the software development lifecycle (SDLC)Develop the skills to trace requirements, from requirements gathering through to implementationPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionExtend your software development skills to integrate security into every aspect of your projects. Perfect for any programmer or developer working on mission-critical applications, this hands-on guide helps you adopt secure software development practices. Explore core concepts like security specifi cation, modeling, and threat mitigation with the iterative approach of this book that allows you to trace security requirements through each phase of software development. You won’t stop at the basics; you’ll delve into multiple-layer att acks and develop the mindset to prevent them. Through an example application project involving an entertainment ticketing software system, you’ll look at high-profi le security incidents that have aff ected popular music stars and performers. Drawing from the author’s decades of experience building secure applications in this domain, this book off ers comprehensive techniques where problem-solving meets practicality for secure development. By the end of this book, you’ll have gained the expertise to systematically secure software projects, from crafting robust security specifi cations to adeptly mitigating multifaceted threats, ensuring your applications stand resilient in the face of evolving cybersecurity challenges.What you will learnFind out non-functional requirements crucial for software security, performance, and reliabilityDevelop the skills to identify and model vulnerabilities in software design and analysisAnalyze and model various threat vectors that pose risks to software applicationsAcquire strategies to mitigate security threats specific to web applicationsAddress threats to the database layer of an applicationTrace non-functional requirements through secure software designWho this book is forMany software development jobs require developing, maintaining, enhancing, administering, and defending software applications, websites, and scripts. This book is designed for software developers and web developers seeking to excel in these roles, offering concise explanations and applied example use-cases.
Engineering Data Mesh in Azure Cloud: Implement data mesh using Microsoft Azure's Cloud Adoption Framework
by Aniruddha DeswandikarOvercome data mesh adoption challenges using the cloud-scale analytics framework and make your data analytics landscape agile and efficient by using standard architecture patterns for diverse analytical workloads Key FeaturesDelve into core data mesh concepts and apply them to real-world situationsSafely reassess and redesign your framework for seamless data mesh integrationConquer practical challenges, from domain organization to building data contractsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionDecentralizing data and centralizing governance are practical, scalable, and modern approaches to data analytics. However, implementing a data mesh can feel like changing the engine of a moving car. Most organizations struggle to start and get caught up in the concept of data domains, spending months trying to organize domains. This is where Engineering Data Mesh in Azure Cloud can help. The book starts by assessing your existing framework before helping you architect a practical design. As you progress, you’ll focus on the Microsoft Cloud Adoption Framework for Azure and the cloud-scale analytics framework, which will help you quickly set up a landing zone for your data mesh in the cloud. The book also resolves common challenges related to the adoption and implementation of a data mesh faced by real customers. It touches on the concepts of data contracts and helps you build practical data contracts that work for your organization. The last part of the book covers some common architecture patterns used for modern analytics frameworks such as artificial intelligence (AI). By the end of this book, you’ll be able to transform existing analytics frameworks into a streamlined data mesh using Microsoft Azure, thereby navigating challenges and implementing advanced architecture patterns for modern analytics workloads.What you will learnBuild a strategy to implement a data mesh in Azure CloudPlan your data mesh journey to build a collaborative analytics platformAddress challenges in designing, building, and managing data contractsGet to grips with monitoring and governing a data meshUnderstand how to build a self-service portal for analyticsDesign and implement a secure data mesh architectureResolve practical challenges related to data mesh adoptionWho this book is forThis book is for chief data officers and data architects of large and medium-size organizations who are struggling to maintain silos of data and analytics projects. Data architects and data engineers looking to understand data mesh and how it can help their organizations democratize data and analytics will also benefit from this book. Prior knowledge of managing centralized analytical systems, as well as experience with building data lakes, data warehouses, data pipelines, data integrations, and transformations is needed to get the most out of this book.
Generating Creative Images With DALL-E 3: Create accurate images with effective prompting for real-world applications
by Holly PicanoLearn to craft fine art prints, NFTs, and captivating covers for books and magazines with Dall-E 3 and ChatGPTKey FeaturesExplore Dall-E 3's diverse practical applications across art, design, education, and beyondMaster AI-generated art creation through step-by-step tutorials, ranging from basic to advanced projectsEnhance your prompt crafting skills with the exclusive prompt cheat sheetPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionUnveil the extraordinary capabilities of the groundbreaking AI model, DALL-E 3, as it transforms text prompts into accurate images. This book addresses the challenge of creating meaningful images by writing prompts, guiding you step by step through creating stunning visual art regardless of your skill level. Prepare to delve deep into the inner workings of DALL-E 3's architecture and training process. With clear explanations, practical tutorials, and real-world examples that can be easily applied, you’ll unlock secrets to creating awe-inspiring AI-generated art, from fine art prints to digital designs. This book provides comprehensive insights into various lens options, camera angles, lighting techniques, and art movements, helping you integrate AI capabilities with your artistic skills. You’ll also learn to create NFTs that can be monetized and gain invaluable insights into designing compelling covers, all within the ethical boundaries of AI-generated art. And with the invaluable prompt cheat sheet by your side, you’ll hone your skills in formulating captivating prompts for diverse purposes. By the end of this book, you’ll have learned how to produce generative AI art at a rapid pace and relatively low cost and push the boundaries of imagination with DALL-E 3.What you will learnMaster DALL-E 3's architecture and training methodsCreate fine prints and other AI-generated art with precisionSeamlessly blend AI with traditional artistryAddress ethical dilemmas in AI artExplore the future of digital creativityImplement practical optimization techniques for your artistic endeavorsWho this book is forWhether you’re an artist looking to integrate AI into your work, a designer seeking new creative horizons, a tech enthusiast intrigued by the intersection of art and artificial intelligence, an educator in the fields of art and technology, or a curious individual venturing into AI-generated art, this book is for you. For anyone interested in the innovative fusion of creativity and technology, the DALL-E 3 Guide to AI Artistry offers invaluable insights and practical skills that you can apply right away.
Machine Learning with Python: Unlocking AI Potential with Python and Machine Learning
by Oliver TheobaldUnlock the secrets of data science and machine learning with our comprehensive Python course, designed to take you from basics to complex algorithms effortlesslyKey FeaturesNavigate through Python's machine learning libraries effectivelyLearn exploratory data analysis and data scrubbing techniquesDesign and evaluate machine learning models with precisionBook DescriptionThe course starts by setting the foundation with an introduction to machine learning, Python, and essential libraries, ensuring you grasp the basics before diving deeper. It then progresses through exploratory data analysis, data scrubbing, and pre-model algorithms, equipping you with the skills to understand and prepare your data for modeling. The journey continues with detailed walkthroughs on creating, evaluating, and optimizing machine learning models, covering key algorithms such as linear and logistic regression, support vector machines, k-nearest neighbors, and tree-based methods. Each section is designed to build upon the previous, reinforcing learning and application of concepts. Wrapping up, the course introduces the next steps, including an introduction to Python for newcomers, ensuring a comprehensive understanding of machine learning applications.What you will learnAnalyze datasets for insightsScrub data for model readinessUnderstand key ML algorithmsDesign and validate modelsApply Linear and Logistic RegressionUtilize K-Nearest Neighbors and SVMsWho this book is forThis course is ideal for aspiring data scientists and professionals looking to integrate machine learning into their workflows. A basic understanding of Python and statistics is beneficial.
C++ High Performance for Financial Systems: Build efficient and optimized financial systems by leveraging the power of C++
by Ariel SilahianAn in-depth guide covering system architecture, low-latency strategies, risk management, and machine learning for experienced programmers looking to enter the financial industry and build high-performance trading systemsKey FeaturesGet started with building financial trading systemsFocus on scalability, architecture, and implementing low-latency network communication in C++Optimize code and use parallel computing techniques for better performancePurchase of the print or Kindle book includes a free PDF eBookBook DescriptionUnlock the secrets of the finance industry and dive into the world of high-performance trading systems with C++ High Performance for Financial Systems. Trading systems are the backbone of the financial world, and understanding how to build them for optimal performance is crucial for success. If you've ever dreamt of creating scalable and cutting-edge financial software, this guide is your key to success. A cornerstone of this book is its coverage of system design and architecture. The book starts by outlining the role of C++ in finance and trading. You'll learn the principles and methodologies behind building systems that can handle vast amounts of data, execute complex trading strategies with ease, and maintain the highest levels of reliability. Armed with this knowledge, you'll be equipped to tackle even the most challenging trading scenarios. In the fast-paced world of finance, every millisecond counts. This book delves into low-latency strategies that will enable your trading systems to react with lightning speed. You’ll also learn the art of reducing latency, optimizing code, and leveraging the latest hardware and software techniques to gain a competitive edge in the market. By the end of this book, you’ll be well-versed in architecting a financial trading system as well as advanced strategies and new industry trends.What you will learnDesign architecture for scalable financial trading systemsUnderstand strategies for low-latency trading and high-frequency tradingDiscover how to implement machine learning algorithms for financial data analysisUnderstand risk management techniques for financial trading systemsExplore advanced topics in finance and trading, including machine learning for algorithmic trading and portfolio optimizationGet up to speed with best practices for developing financial trading systems with C++Who this book is forThis book is for experienced C++ developers who want to enter the finance industry and learn how trading systems work. It is also suitable for quantitative analysts, financial engineers, and anyone interested in building scalable and robust trading systems. The book assumes familiarity with the C++ programming language, data structures, and algorithms. Additionally, readers should have a basic understanding of finance and trading concepts, such as market data, trading strategies, and risk management.
Dancing with Qubits: From qubits to algorithms, embark on the quantum computing journey shaping our future
by Robert S. SutorUnlock the core math and understand the technical nuances of quantum computing in this detailed guide. Delve into the practicality of NISQ algorithms, and survey promising advancements in quantum machine learning.Key FeaturesDiscover how quantum computing works and delve into the math behind it with practical examplesLearn about and assess the most up-to-date quantum computing topics including quantum machine learningExplore the inner workings of existing quantum computing technologies to understand how they may perform significantly better than their classical counterpartsBook DescriptionDancing with Qubits, Second Edition, is a comprehensive quantum computing textbook that starts with an overview of why quantum computing is so different from classical computing and describes several industry use cases where it can have a major impact. A full description of classical computing and the mathematical underpinnings of quantum computing follows, helping you better understand concepts such as superposition, entanglement, and interference. Next up are circuits and algorithms, both basic and sophisticated, as well as a survey of the physics and engineering ideas behind how quantum computing hardware is built. Finally, the book looks to the future and gives you guidance on understanding how further developments may affect you. This new edition is updated throughout with more than 100 new exercises and includes new chapters on NISQ algorithms and quantum machine learning. Understanding quantum computing requires a lot of math, and this book doesn't shy away from the necessary math concepts you'll need. Each topic is explained thoroughly and with helpful examples, leaving you with a solid foundation of knowledge in quantum computing that will help you pursue and leverage quantum-led technologies.What you will learnExplore the mathematical foundations of quantum computingDiscover the complex, mind-bending concepts that underpin quantum systemsUnderstand the key ideas behind classical and quantum computingRefresh and extend your grasp of essential mathematics, computing, and quantum theoryExamine a detailed overview of qubits and quantum circuitsDive into quantum algorithms such as Grover’s search, Deutsch-Jozsa, Simon’s, and Shor’sExplore the main applications of quantum computing in the fields of scientific computing, AI, and elsewhereWho this book is forDancing with Qubits, Second Edition, is a quantum computing textbook for all those who want to understand and explore the inner workings of quantum computing. This entails building up from basic to some sophisticated mathematics and is therefore best suited for those with a healthy interest in mathematics, physics, engineering, or computer science.
Mastering Go: Leverage Go's expertise for advanced utilities, empowering you to develop professional software
by Mihalis TsoukalosDive into the core of Go programming and cover advanced topics like generics, concurrency, web services, and cutting-edge testing techniques in this comprehensive fourth edition.Key FeaturesFully updated with coverage of web services, TCP/IP, REST APIs, Go Generics, and Fuzzy TestingApply your new knowledge to real-world exercises, building high-performance servers and robust command-line utilities, to deepen your learningGain clarity on what makes Go different, understand its nuances and features for smoother Go developmentBook DescriptionMastering Go, now in its fourth edition, remains the go-to resource for real-world Go development. This comprehensive guide delves into advanced Go concepts, including RESTful servers, and Go memory management. This edition brings new chapters on Go Generics and fuzzy Testing, and an enriched exploration of efficiency and performance. As you work your way through the chapters, you will gain confidence and a deep understanding of advanced Go topics, including concurrency and the operation of the Garbage Collector, using Go with Docker, writing powerful command-line utilities, working with JavaScript Object Notation (JSON) data, and interacting with databases. You will be engaged in real-world exercises, build network servers, and develop robust command-line utilities. With in-depth chapters on RESTful services, the WebSocket protocol, and Go internals, you are going to master Go's nuances, optimization, and observability. You will also elevate your skills in efficiency, performance, and advanced testing. With the help of Mastering Go, you will become an expert Go programmer by building Go systems and implementing advanced Go techniques in your projects.What you will learnLearn Go data types, error handling, constants, pointers, and array and slice manipulations through practical exercisesCreate generic functions, define data types, explore constraints, and grasp interfaces and reflectionsGrasp advanced concepts like packages, modules, functions, and database interactionCreate concurrent RESTful servers, and build TCP/IP clients and serversLearn testing, profiling, and efficient coding for high-performance applicationsDevelop an SQLite package, explore Docker integration, and embrace workspacesWho this book is forMastering Go is written primarily for Go programmers who have some experience with the language and want to become expert practitioners. You will need to know the basics of computer programming before you get started with this book, but beyond that, anyone can sink their teeth into it.
Google Cloud Digital Leader Certification Guide: A comprehensive study guide to Google Cloud concepts and technologies
by Bruno Beraldo RodriguesGain the expertise needed for the Google Cloud Digital Leader certification with the help of industry insights, effective testing strategies, and exam questions designed to help you make informed tech decisions aligned with business goalsKey FeaturesLearn about data management, AI, monetization, security, and the significance of infrastructure modernizationBuild a solid foundation in Google Cloud, covering all technical essentials necessary for a Google Cloud Digital LeaderTest your knowledge of cloud and digital transformation through realistic exam questionsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionTo thrive in today's world, leaders and technologists must understand how technology shapes businesses. As organizations shift from self-hosted to cloud-native solutions, embracing serverless systems, strategizing data use, and defining monetization becomes imperative. The Google Cloud Digital Leader Certification Guide lays a solid foundation of industry knowledge, focused on the Google Cloud platform and the innovative ways in which customers leverage its technologies. The book starts by helping you grasp the essence of digital transformation within the Google Cloud context. You’ll then cover core components of the platform, such as infrastructure and application modernization, data innovation, and best practices for environment management and security. With a series of practice exam questions included, this book ensures that you build comprehensive knowledge and prepare to certify as a Google Cloud Digital Leader. Going beyond the exam essentials, you’ll also explore how companies are modernizing infrastructure, data ecosystems, and teams in order to capitalize on new market opportunities through platform expertise, best practices, and real-world scenarios. By the end of this book, you'll have learned everything you need to pass the Google Cloud Digital Leader certification exam and have a reference guide for future requirements.What you will learnLeverage Google Cloud’s AI and ML solutions to create business valueIdentify Google Cloud solutions for data management and smart analyticsAcquire the skills necessary to modernize infrastructure and applications on GCPUnderstand the value of APIs and their applications in cloud environmentsMaster financial governance and implement best practices for cost managementUnderstand the cloud security approach and benefits of Google Cloud securityFind out how IT operations must adapt to thrive in the cloudWho this book is forThis Google Cloud fundamentals book is suitable for individuals with both technical and non-technical backgrounds looking for a starting point to pursue more advanced Google Cloud certifications. No prior experience is required to get started with this book; only a keen interest in learning and exploring cloud concepts, with a focus on Google Cloud.
Generative AI Art: Unleash Your Creativity with Generative AI Art for Beginners
by Oliver TheobaldDive into the realm of AI art with our beginner's course, empowering you to create ethically and originally, and unlock a new horizon of digital creativityKey FeaturesExplore the basics of AI and art integrationNavigate through AI art software with easeEnhance artworks using AI-driven techniquesBook DescriptionThe course introduces the basic concepts of artificial intelligence and its application in art, making it accessible even to those without a technical background. This foundation paves the way for exploring the nuances of effective prompt crafting, a critical skill for generating bespoke AI artwork. The course focuses on hands-on demonstrations with leading AI art software, including Craiyon and Midjourney, offering step-by-step guides to harness these tools effectively. Through practical examples, learners will understand how to navigate image prompts, masking techniques, framing, and lighting to enhance the visual appeal of their creations. The significance of navigating these elements is underscored, highlighting their role in achieving consistency and originality in AI-generated art. The course wraps up by delving into the remixing of popular art styles, the art of creating compelling text prompts, and the critical aspects of image rights, ethics, privacy, and originality in the digital art space. By concluding with recommended resources, learners are equipped to continue their journey in AI art, fueled by inspiration and a solid understanding of the field's possibilities and responsibilities.What you will learnUnderstand AI's role in creating artCraft effective AI prompts for art generationNavigate leading AI art software toolsWho this book is forThis course is ideal for artists, creatives, and anyone intrigued by the intersection of technology and art. No prior experience in AI or art is required, making it perfect for beginners eager to explore the capabilities of generative AI art and embrace digital creativity.
LaTeX für Dummies (Für Dummies)
by Rainer Griesbaum Ivica RoginaLaTeX lernen leicht gemacht Von der Installation bis zum Druck: Rainer Griesbaum und Ivica Rogina erklären Ihnen in diesem Buch alles, was Sie zu dem bei Mathematikern, Naturwissenschaftlern und Ingenieuren beliebten Textsatzsystem LaTeX wissen müssen. Bringen Sie mit LaTeX umfangreiche Texte elegant in Form und integrieren Sie anschauliche Abbildungen, übersichtliche Tabellen, informative Fu?noten und schön gestaltete mathematische Formeln. Im Handumdrehen haben Sie ein Inhaltsverzeichnis erstellt, ein Register angelegt oder eine ansprechende Präsentation aufgebaut. Das alles können Sie mit dem Online- Editor Overleaf auch im Internet erledigen, alleine oder gemeinsam mit anderen. Sie erfahren Wie Sie LaTeX und eine bersichtliche Arbeitsumgebung einrichten Wie Sie Texte formatieren, Tabellen erstellen oder Formeln setzen Wie Sie Dokumente strukturieren, Verzeichnisse erstellen und Abbildungen einbinden
Computational Design: Technology, Cognition and Environments
by Rongrong Yu Ning Gu Michael J. OstwaldNew computational design tools have evolved rapidly and been increasingly applied in the field of design in recent years, complimenting and even replacing the traditional design media and approaches. Design as both the process and product are changing due to the emergence and adoption of these new technologies. Understanding and assessing the impact of these new computational design environments on design and designers is important for advancing design in the contemporary context. Do these new computational environments support or hinder design creativity? How do those tools facilitate designers’ thinking? Such knowledge is also important for the future development of design technologies. Research shows that design is never a mysterious non-understandable process, for example, one general view is that design process shares a common analysis-synthesis-evaluation model, during which designers interact between design problem and solution spaces. Understanding designers’ thinking in different environments is the key to design research, education and practice. This book focuses on emerging computational design environments, whose impact on design and designers have not been comprehensively and systematically studied. It comprises three parts. The history and recent developments of computational design technologies are introduced in Part I. The main categories of technologies cover from computer-aided drafting and modelling tools, to visual programming and scripting tools for algorithmic design, to advanced interfaces and platforms for interactions between designers, between designers and computers, and between the virtual environment and the physical reality. To critically explore design thinking, especially in these new computational design environments, formal approaches to studying design thinking and design cognition are introduced and compared in Part II, drawing on literature and studies from the 70s to the current era. Part III concludes the book by exploring the impact of different computational design technologies on design and designers, using a series of case studies conducted by the author team building on their close collaboration over the past five years. The book offers new insights into designers’ thinking in the rapidly evolving computational design environments, which have not been critically and systematically studied and reported in the current literature. The book is meant for design researchers, educators and students, professional practitioners and consultants, as well as people who are interested in computational design in general.
Cyber Operations: A Case Study Approach
by Jerry M. CouretasCyber Operations A rigorous new framework for understanding the world of the future Information technology is evolving at a truly revolutionary pace, creating with every passing year a more connected world with an ever-expanding digital footprint. Cyber technologies like voice-activated search, automated transport, and the Internet of Things are only broadening the interface between the personal and the online, which creates new challenges and new opportunities. Improving both user security and quality of life demands a rigorous, farsighted approach to cyber operations. Cyber Operations offers a groundbreaking contribution to this effort, departing from earlier works to offer a comprehensive, structured framework for analyzing cyber systems and their interactions. Drawing on operational examples and real-world case studies, it promises to provide both cyber security professionals and cyber technologies designers with the conceptual models and practical methodologies they need to succeed. Cyber Operations readers will also find: Detailed discussions of case studies including the 2016 United States Presidential Election, the Dragonfly Campaign, and more Coverage of cyber attack impacts ranging from the psychological to attacks on physical infrastructure Insight from an author with top-level experience in cyber security Cyber Operations is ideal for all technological professionals or policymakers looking to develop their understanding of cyber issues.
Cyber Operations: A Case Study Approach
by Jerry M. CouretasCyber Operations A rigorous new framework for understanding the world of the future Information technology is evolving at a truly revolutionary pace, creating with every passing year a more connected world with an ever-expanding digital footprint. Cyber technologies like voice-activated search, automated transport, and the Internet of Things are only broadening the interface between the personal and the online, which creates new challenges and new opportunities. Improving both user security and quality of life demands a rigorous, farsighted approach to cyber operations. Cyber Operations offers a groundbreaking contribution to this effort, departing from earlier works to offer a comprehensive, structured framework for analyzing cyber systems and their interactions. Drawing on operational examples and real-world case studies, it promises to provide both cyber security professionals and cyber technologies designers with the conceptual models and practical methodologies they need to succeed. Cyber Operations readers will also find: Detailed discussions of case studies including the 2016 United States Presidential Election, the Dragonfly Campaign, and more Coverage of cyber attack impacts ranging from the psychological to attacks on physical infrastructure Insight from an author with top-level experience in cyber security Cyber Operations is ideal for all technological professionals or policymakers looking to develop their understanding of cyber issues.
Building Cybersecurity Applications with Blockchain and Smart Contracts (Signals and Communication Technology)
by Nour El Madhoun Ioanna Dionysiou Emmanuel BertinThis book offers an in-depth exploration of the application of blockchain and smart contract technologies in the field of cybersecurity. It begins by defining the fundamentals of cybersecurity in the context of blockchain and smart contracts, and then moves on to the world of e-government services, describing how blockchain can enhance the security of these services. The book also explores how blockchain can secure the Internet of Things (IoT), focusing on applications such as securing drones and protecting robotic networks. The importance of scalability in distributed replication systems is also discussed, with a particular focus on sharding. Finally, the book looks at the challenges of data protection in distributed ledger and blockchain technologies, providing both an analysis of the problems and solutions. Written by academic researchers and industry experts, this book offers a comprehensive and nuanced perspective on the transformational potential of blockchain and smart contracts in the field of cybersecurity.
Data Mining with Python: Theory, Application, and Case Studies (Chapman & Hall/CRC The Python Series)
by Di WuData is everywhere and it’s growing at an unprecedented rate. But making sense of all that data is a challenge. Data Mining is the process of discovering patterns and knowledge from large data sets, and Data Mining with Python focuses on the hands-on approach to learning Data Mining. It showcases how to use Python Packages to fulfill the Data Mining pipeline, which is to collect, integrate, manipulate, clean, process, organize, and analyze data for knowledge.The contents are organized based on the Data Mining pipeline, so readers can naturally progress step by step through the process. Topics, methods, and tools are explained in three aspects: “What it is” as a theoretical background, “why we need it” as an application orientation, and “how we do it” as a case study.This book is designed to give students, data scientists, and business analysts an understanding of Data Mining concepts in an applicable way. Through interactive tutorials that can be run, modified, and used for a more comprehensive learning experience, this book will help its readers to gain practical skills to implement Data Mining techniques in their work.Dr. Di Wu is an Assistant Professor of Finance, Information Systems, and Economics department of Business School, Lehman College. He obtained a Ph.D. in Computer Science from the Graduate Center, CUNY. Dr. Wu’s research interests are Temporal extensions to RDF and semantic web, Applied Data Science, and Experiential Learning and Pedagogy in Business Education. Dr. Wu developed and taught courses including Strategic Management, Databases, Business Statistics, Management Decision Making, Programming Languages (C++, Java, and Python), Data Structures and Algorithms, Data Mining, Big Data, and Machine Learning.
Data Mining with Python: Theory, Application, and Case Studies (Chapman & Hall/CRC The Python Series)
by Di WuData is everywhere and it’s growing at an unprecedented rate. But making sense of all that data is a challenge. Data Mining is the process of discovering patterns and knowledge from large data sets, and Data Mining with Python focuses on the hands-on approach to learning Data Mining. It showcases how to use Python Packages to fulfill the Data Mining pipeline, which is to collect, integrate, manipulate, clean, process, organize, and analyze data for knowledge.The contents are organized based on the Data Mining pipeline, so readers can naturally progress step by step through the process. Topics, methods, and tools are explained in three aspects: “What it is” as a theoretical background, “why we need it” as an application orientation, and “how we do it” as a case study.This book is designed to give students, data scientists, and business analysts an understanding of Data Mining concepts in an applicable way. Through interactive tutorials that can be run, modified, and used for a more comprehensive learning experience, this book will help its readers to gain practical skills to implement Data Mining techniques in their work.Dr. Di Wu is an Assistant Professor of Finance, Information Systems, and Economics department of Business School, Lehman College. He obtained a Ph.D. in Computer Science from the Graduate Center, CUNY. Dr. Wu’s research interests are Temporal extensions to RDF and semantic web, Applied Data Science, and Experiential Learning and Pedagogy in Business Education. Dr. Wu developed and taught courses including Strategic Management, Databases, Business Statistics, Management Decision Making, Programming Languages (C++, Java, and Python), Data Structures and Algorithms, Data Mining, Big Data, and Machine Learning.