Computer & IT

"Earning Online: From Side Hustle to Full-Time Income" is a comprehensive guide for anyone looking to leverage the power of the internet to create a sustainable and profitable online income stream. Whether you're a freelancer, entrepreneur, or someone simply looking to earn extra money, this book provides practical advice, proven strategies, and actionable steps to help you build a successful online business.From identifying your niche and setting up your online presence to attracting customers and maximizing your profits, "Earning Online" covers every aspect of starting and growing a profitable online business. With insights from successful online entrepreneurs and case studies illustrating real-world examples, this book equips you with the knowledge and tools you need to turn your online venture into a thriving full-time income.

A book for the aspiring .NET software architect - design scalable and high-performance enterprise solutions using the latest features of C# 12 and .NET 8Purchase of the print or Kindle book includes a free PDF eBookKey FeaturesGet introduced to software architecture fundamentals and begin applying them in .NETExplore the main technologies used by software architects and choose the best ones for your needsMaster new developments in .NET with the help of a practical case study that looks at software architecture for a travel agencyBook DescriptionSoftware Architecture with C# 12 and .NET 8 puts high-level design theory to work in a .NET context, teaching you the key skills, technologies, and best practices required to become an effective .NET software architect.This fourth edition puts emphasis on a case study that will bring your skills to life. You'll learn how to choose between different architectures and technologies at each level of the stack. You'll take an even closer look at Blazor and explore OpenTelemetry for observability, as well as a more practical dive into preparing .NET microservices for Kubernetes integration.Divided into three parts, this book starts with the fundamentals of software architecture, covering C# best practices, software domains, design patterns, DevOps principles for CI/CD, and more. The second part focuses on the technologies, from choosing data storage in the cloud to implementing frontend microservices and working with Serverless. You'll learn about the main communication technologies used in microservices, such as REST API, gRPC, Azure Service Bus, and RabbitMQ. The final part takes you through a real-world case study where you'll create software architecture for a travel agency.By the end of this book, you will be able to transform user requirements into technical needs and deliver highly scalable enterprise software architectures.What you will learnProgram and maintain Azure DevOps and explore GitHub ProjectsManage software requirements to design functional and non-functional needsApply architectural approaches such as layered architecture and domain-driven designMake effective choices between cloud-based and data storage solutionsImplement resilient frontend microservices, worker microservices, and distributed transactionsUnderstand when to use test-driven development (TDD) and alternative approachesChoose the best option for cloud development, from IaaS to ServerlessWho this book is forThis book is for engineers and senior software developers aspiring to become architects or looking to build enterprise applications with the .NET stack.Basic familiarity with C# and .NET is required to get the most out of this software architecture book.Table of ContentsUnderstanding the Importance of Software ArchitectureNon-Functional RequirementsManaging RequirementsBest Practices in Coding C# 12Implementing Code Reusability in C# 12Design Patterns and .NET 8 ImplementationUnderstanding the Different Domains in Software SolutionsUnderstanding DevOps Principles and CI/CDTesting Your Enterprise ApplicationDeciding on the Best Cloud-Based SolutionApplying a Microservice Architecture to Your Enterprise ApplicationChoosing Your Data Storage in the cloudInteracting with Data in C# - Entity Framework CoreImplementing Microservices with .NETApplying Service-Oriented Architectures with .NETWorking with Serverless - Azure FunctionsPresenting ASP.NET Core(N.B. Please use the Look Inside option to see further chapters)

In this stimulating journey of Rust, you'll learn how to use the Rust programming language in conjunction with machine learning. It's not a full guide to learning machine learning with Rust. Instead, it's more of a journey that shows you what's possible when you use Rust to solve machine learning problems. Some people like Rust because it is quick and safe. This book shows how those qualities can help machine learning a lot.To begin, we will show you what Rust is and how it works. This is so that everyone, even those who are new to Rust, can follow along. Then, we look at some basic machine learning concepts, such as linear and logistic regression, and show how to use Rust's tools and libraries to make these ideas work.You will learn more complex techniques like decision trees, support vector machines, and how to work with data as we go along. It goes all the way up to neural networks and image recognition, and we show you how to use Rust for these types of tasks step by step. We use real-world examples, such as COVID data and the CIFAR-10 image set, to show how Rust works with issues that come up in the real world.This book is all about discovery and experimentation. To see what you can do with them, we use various Rust tools for machine learning. It's a fun way to see how Rust can be used in machine learning, and it will make you want to try new things and learn more on your own. This is only the beginning; there is so much more to uncover as you continue to explore machine learning with Rust. Key LearningsExploit Rust's efficiency and safety to construct fast machine learning models.Use Rust's ndarray crate for numerical computations to manipulate complex machine learning data.Find out how Rust's extensible machine learning framework, linfa, works across algorithms.Use Rust's precision and speed to construct linear and logistic regression.See how Rust crates simplify decision trees and random forests for prediction and categorization.Learn to implement and optimize probabilistic classifiers, SVMs and closest neighbor methods in Rust.Use Rust's computing power to study neural networks and CNNs for picture recognition and processing.Apply learnt strategies to COVID and CIFAR-10 datasets to address realistic problems and obtain insights. Table of ContentRust Basics for Machine LearningData Wrangling with RustLinear Regression by ExampleLogistic Regression for ClassificationDecision Trees in ActionMastering Random ForestsSupport Vector Machines in ActionSimplifying Naive Bayes and k-NNCrafting Neural Networks with Rust

Elevate your test automation skills by mastering Selenium with Java, delving into advanced techniques for a comprehensive understanding.Book DescriptionThis comprehensive and practical handbook, centered on Selenium unlocks its potential using Java. The book covers Selenium basics, including IDE and WebDriver, while delving into advanced topics like Selenium Grid and non-functional test automation. It will help you take your automation to the next level by gaining insights into creating Hybrid test automation frameworks with practical applications of TestNG. Real-world insights from industry leaders enrich the learning experience, transcending tool proficiency to strategic test automation and framework design. With practical examples and case studies from diverse sectors, including banking, healthcare, e-commerce, and SAAS, the book showcases Selenium's real-world applications.By the end of the book, you will extend Selenium's capabilities for Performance, Security, and Excel-based automation. The book will help you stay ahead in the ever-evolving field with insights into the latest updates, including Selenium Manager, BiDi protocol, network interception, relative locators, and Selenium's roadmap.Table of Contents1. Introduction to Selenium Test Automation2. Fundamentals of Test Automation3. Selenium WebDriver Basics4. Advanced Selenium Techniques5. Test Automation Framework6. Distributed Test Automation7. SAAS and Non-functional Test Automation8. BDD with Selenium9. New Features in Selenium 410. Conclusion11. Way Forward Index

Delve into the inner workings of JVM and explore internals, memory management, and performance optimizationKey Features:- Uncover the intricacies of JVM, from class loading to garbage collection, and more- Master JVM memory management for efficient resource use and reduced overhead- Apply JVM knowledge through case studies, reinforcing your understanding of internals- Purchase of the print or Kindle book includes a free PDF eBookBook Description:Mastering the Java Virtual Machine is a comprehensive guide that will take you into the heart of the Java programming language, guiding you through the intricate workings of the Java Virtual Machine (JVM) and equipping you with essential skills to become a proficient Java developer.You'll start by understanding the JVM, exploring its architecture and how it executes Java code. Through detailed explanations and real-world examples, you'll gain a deep understanding of JVM internals, enabling you to write efficient and optimized Java applications. As you progress, you'll delve into memory management and execution, unraveling the complexities of heap and stack management, garbage collection, and memory profiling. You'll learn how memory is allocated and reclaimed in the JVM, as well as how to optimize memory usage and identify performance bottlenecks in your applications. With this knowledge, you'll be able to create Java programs that are not only robust but also highly performant.By the end of this Java book, you'll have the skills needed to excel in Java programming, writing efficient and maintainable code.What You Will Learn:- Understand JVM architecture and bytecode execution- Explore memory management and optimize memory usage- Compare and evaluate alternative JVMs like GraalVM- Master reflection for dynamic behavior in Java applications- Use Java annotation processors for code generation- Get to grips with reactive programming principles for scalable applicationsWho this book is for:This book is for Java developers looking to deepen their expertise in the Java Virtual Machine (JVM) and optimize Java applications for peak performance. It is ideal for both intermediate-level and seasoned professionals, who want to explore specific aspects such as JVM internals, memory management, threading, security, and performance tuning.Table of Contents- Introduction to the Java Virtual Machine- Class File Structure- Understanding Bytecodes- Memory Management- Execution Engine- Class Loading and Dynamic Class Loading- Garbage Collection and Memory Profiling- GraalVM- JVM Ecosystem and Alternative JVMs- Java Framework Principles- Reflection- Java Annotation Processor

Unlock the full potential of your data by mastering the art of cleaning, preparing, and transforming data with Power BI for smarter insights and data visualizationsKey Features:Implement best practices for connecting, preparing, cleaning, and analyzing multiple sources of data using Power BIConduct exploratory data analysis (EDA) using DAX, PowerQuery, and the M languageApply your newfound knowledge to tackle common data challenges for visualizations in Power BIPurchase of the print or Kindle book includes a free PDF eBookBook Description:Microsoft Power BI offers a range of powerful data cleaning and preparation options through tools such as DAX, Power Query, and the M language. However, despite its user-friendly interface, mastering it can be challenging. Whether you're a seasoned analyst or a novice exploring the potential of Power BI, this comprehensive guide equips you with techniques to transform raw data into a reliable foundation for insightful analysis and visualization.This book serves as a comprehensive guide to data cleaning, starting with data quality, common data challenges, and best practices for handling data. You'll learn how to import and clean data with Query Editor and transform data using the M query language. As you advance, you'll explore Power BI's data modeling capabilities for efficient cleaning and establishing relationships. Later chapters cover best practices for using Power Automate for data cleaning and task automation. Finally, you'll discover how OpenAI and ChatGPT can make data cleaning in Power BI easier.By the end of the book, you will have a comprehensive understanding of data cleaning concepts, techniques, and how to use Power BI and its tools for effective data preparation.What You Will Learn:Connect to data sources using both import and DirectQuery optionsUse the Query Editor to apply data transformationsTransform your data using the M query languageDesign clean and optimized data models by creating relationships and DAX calculationsPerform exploratory data analysis using Power BIAddress the most common data challenges with best practicesExplore the benefits of using OpenAI, ChatGPT, and Microsoft Copilot for simplifying data cleaningWho this book is for:If you're a data analyst, business intelligence professional, business analyst, data scientist, or anyone who works with data on a regular basis, this book is for you. It's a useful resource for anyone who wants to gain a deeper understanding of data quality issues and best practices for data cleaning in Power BI. If you have a basic knowledge of BI tools and concepts, this book will help you advance your skills in Power BI.

Explore practical LaTeX examples across various fields like mathematics, physics, chemistry, and computer science, and learn to quickly create tables, diagrams, and plots for your thesis, presentations, and articlesKey Features:- Work with ready-to-use document templates to write articles, books, a thesis, and more- Refine text, fonts, formulas, and tables, and optimize PDF properties- Create captivating graphics directly within LaTeX in 2D and 3D- Purchase of the print or Kindle book includes a free PDF eBookBook Description:The second edition of LaTeX Cookbook offers improved and additional examples especially for users in science and academia, with a focus on new packages for creating graphics with LaTeX. This edition also features an additional chapter on ChatGPT use to improve content, streamline code, and automate tasks, thereby saving time. This book is a practical guide to utilizing the capabilities of modern document classes and exploring the functionalities of the newest LaTeX packages. Starting with familiar document types like articles, books, letters, posters, leaflets, and presentations, it contains detailed tutorials for refining text design, adjusting fonts, managing images, creating tables, and optimizing PDFs. It also covers elements such as the bibliography, glossary, and index. You'll learn to create graphics directly within LaTeX, including diagrams and plots, and explore LaTeX's application across various fields like mathematics, physics, chemistry, and computer science. The book's website offers online compilable code, an example gallery, and supplementary information related to the book, including the author's LaTeX forum, where you can get personal support. By the end of this book, you'll have the skills to optimize productivity through practical demonstrations of effective LaTeX usage in diverse scenarios.What You Will Learn:- Utilize various document classes and incorporate bibliography, glossary, and index sections- Handle arranging and annotating images with ease- Create visually appealing tables and learn how to manage fonts efficiently- Generate diverse and colorful graphics, including diagrams, flow charts, bar charts, trees, and both 2D and 3D plots- Solve writing and drawing tasks across various scientific disciplines- Optimize PDF output, enhancing it with metadata, annotations, popups, animations, and fill-in fields- Leverage ChatGPT to improve content and codeWho this book is for:If you're a LaTeX user in school, academia, or industry with a foundational understanding of LaTeX basics, this book offers efficient solutions to expedite your tasks. Tailored to students, teachers, authors, and engineers, its example-driven format enables quick access to solutions. Familiarity with basic LaTeX syntax and using LaTeX with your preferred editor for compiling is recommended to make the most of this book.Table of Contents- Exploring Various Document Classes- Tuning the Text- Adjusting Fonts- Creating Tables- Working with Images- Creating Graphics- Creating Beautiful Designs- Producing Contents, Indexes, and Bibliographies- Optimizing PDF Files- Writing Advanced Mathematics- Using LaTeX in Science and Technology- Getting Support on the Internet- Using Artificial Intelligence with LaTeX

Prepare confidently for the AWS MLS-C01 certification with this comprehensive and up-to-date exam guide, accompanied by web-based tools such as mock exams, flashcards, and exam tipsKey Features:Gain proficiency in AWS machine learning services to excel in the MLS-C01 examBuild model training and inference pipelines and deploy machine learning models to the AWS cloudPractice on the go with the mobile-friendly bonus website, accessible with the bookPurchase of the print or Kindle book includes a free PDF eBookBook Description:The AWS Certified Machine Learning Specialty (MLS-C01) exam evaluates your ability to execute machine learning tasks on AWS infrastructure. This comprehensive book aligns with the latest exam syllabus, offering practical examples to support your real-world machine learning projects on AWS. Additionally, you'll get lifetime access to supplementary online resources, including mock exams with exam-like timers, detailed solutions, interactive flashcards, and invaluable exam tips, all accessible across various devices-PCs, tablets, and smartphones.Throughout the book, you'll learn data preparation techniques for machine learning, covering diverse methods for data manipulation and transformation across different variable types. Addressing challenges such as missing data and outliers, the book guides you through an array of machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, text mining, and image processing, accompanied by requisite machine learning algorithms essential for exam success. The book helps you master the deployment of models in production environments and their subsequent monitoring.Equipped with insights from this book and the accompanying mock exams, you'll be fully prepared to achieve the AWS MLS-C01 certification.What You Will Learn:Identify ML frameworks for specific tasksApply CRISP-DM to build ML pipelinesCombine AWS services to build AI/ML solutionsApply various techniques to transform your data, such as one-hot encoding, binary encoder, ordinal encoding, binning, and text transformationsVisualize relationships, comparisons, compositions, and distributions in the dataUse data preparation techniques and AWS services for batch and real-time data processingCreate training and inference ML pipelines with Sage MakerDeploy ML models in a production environment efficientlyWho this book is for:This book is designed for both students and professionals preparing for the AWS Certified Machine Learning Specialty exam or enhance their understanding of machine learning, with a specific emphasis on AWS. Familiarity with machine learning basics and AWS services is recommended to fully benefit from this book.

Meta Description: With a wealth of practical recipes, this third edition isn't just a guide to C++23; it's a complete resource covering key features and techniques from C++11 through to C++23. It's designed to keep you ahead of the curve in C++.Key Features:- Updated and packed with new recipes, including sync streams, std:expected and std:mdspan, and C++20/23 range adaptors- Covers all significant features from all modern versions of the standard, providing comprehensive insights into modern C++- Learn through a series of hands-on, self-contained recipes- Purchase of the print or Kindle book includes a free eBook in PDF formatBook Description:The updated third edition of Modern C++ Programming Cookbook addresses the latest features of C++23, such as the stacktrace library, std::expected and std::mdspan classes, the header, formatting library improvements, and updates to the ranges library. It also gets into more C++20 topics not previously covered, such as sync streams and source_location.The book is organized into practical recipes covering a wide range of real-world problems, helping you find the solutions you need quickly. You'll find coverage of all the core concepts of modern C++ programming and features and techniques from C++11 through to C++23, meaning you'll stay ahead of the curve by learning to incorporate the newest language and library improvements.Beyond the core concepts and new features, you'll explore recipes related to performance and best practices, how to implement useful patterns and idioms, like pimpl, named parameter, attorney-client, and the factory pattern, and how to complete unit testing with the widely used C++ libraries: Boost.Test, Google Test, and Catch2.With the comprehensive coverage this C++ programming guide offers, by the end of the book you'll have everything you need to build performant, scalable, and efficient applications in C++.What You Will Learn:- Explore the new C++23 language and library features- Go deep into the most useful C++20 features- Learn to handle threading and concurrency for better performance- Solve complex string manipulation tasks efficiently with regex- Leverage the standard library for faster development- Master the filesystem library to work with files and directories- Work with different types of strings and understand compilation- See how you can use CRTP, mixins and other patterns in C++Who this book is for:This book is designed for entry- and intermediate-level programmers who already have a foundational understanding of the C++ programming language, but who are looking to master the language, implement the newest features, and become proficient modern C++ developers. Experienced C++ programmers can leverage the recipes in this book to quickly get up to speed on all the most important language and library features of C++11/14/17/20 and 23.Table of Contents- Learning Modern Core Language Features- Working with Numbers and Strings- Exploring Functions- Preprocessing and Compilation- Standard Library Containers, Algorithms, and Iterators- General-Purpose Utilities- Working with Files and Streams- Leveraging Threading and Concurrency- Robustness and Performance- Implementing Patterns and Idioms- Exploring Testing Frameworks- C++23 Features

Harness the power of Microsoft Fabric to develop data analytics solutions for various use cases guided by step-by-step instructionsKey FeaturesExplore Microsoft Fabric and its features through real-world examplesBuild data analytics solutions for lakehouses, data warehouses, real-time analytics, and data scienceMonitor, manage, and administer your Fabric platform and analytics system to ensure flexibility, performance, security, and controlPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionDiscover the capabilities of Microsoft Fabric, the premier unified solution designed for the AI era, seamlessly combining data integration, OneLake, transformation, visualization, universal security, and a unified business model. This book provides an overview of Microsoft Fabric, its components, and the wider analytics landscape.In this book, you'll explore workloads such as Data Factory, Synapse Data Engineering, data science, data warehouse, real-time analytics, and Power BI. You'll learn how to build end-to-end lakehouse and data warehouse solutions using the medallion architecture, unlock the real-time analytics, and implement machine learning and AI models. As you progress, you'll build expertise in monitoring workloads and administering Fabric across tenants, capacities, and workspaces. The book also guides you step by step through enhancing security and governance practices in Microsoft Fabric and implementing CI/CD workflows with Azure DevOps or GitHub. Finally, you'll discover the power of Copilot, an AI-driven assistant that accelerates your analytics journey.By the end of this book, you'll have unlocked the full potential of AI-driven data analytics, gaining a comprehensive understanding of the analytics landscape and mastery over the essential concepts and principles of Microsoft Fabric.What you will learnGet acquainted with the different services available in Microsoft FabricBuild end-to-end data analytics solution to scale and manage high performanceIntegrate data from different types of data sourcesApply transformation with Spark, Notebook, and T-SQLUnderstand and implement real-time stream processing and data science capabilitiesPerform end-to-end processes for building data analytics solutions in the AI eraDrive insights by leveraging Power BI for reporting and visualizationImprove productivity with AI assistance and Copilot integrationWho this book is forThis book is for data professionals, including data analysts, data engineers, data scientists, data warehouse developers, ETL developers, business analysts, AI/ML professionals, software developers, and Chief Data Officers who want to build a future-ready data analytics solution for long-term success in the AI era.For PySpark and SQL students entering the data analytics field, this book offers a broad foundation for developing the skills to build end-to-end analytics systems for various use cases. Basic knowledge of SQL and Spark is assumed.Table of ContentsOverview of Microsoft Fabric and Understanding Its Different ConceptsUnderstanding Different Workloads and Getting Started with Microsoft Fabric Building an End-to-End Analytics System - LakehouseBuilding an End-to-End Analytics System - Data WarehouseBuilding an End-to-End Analytics System - Real-Time AnalyticsBuilding an End-to-End Analytics System - Data ScienceMonitoring Overview and Monitoring Different WorkloadsAdministering FabricSecurity and Governance Overview(N.B. Please use the Look Inside option to see further chapters)

A practical guide to deploying, managing, and leveraging the power of Microsoft's unified security solutionKey Features- Learn how to leverage Microsoft's XDR and SIEM for long-term resilience- Explore ways to elevate your security posture using Microsoft Defender tools such as MDI, MDE, MDO, MDA, and MDC- Discover strategies for proactive threat hunting and rapid incident response- Purchase of the print or Kindle book includes a free PDF eBookBook DescriptionTired of dealing with fragmented security tools and navigating endless threat escalations? Take charge of your cyber defenses with the power of Microsoft's unified XDR and SIEM solution.This comprehensive guide offers an actionable roadmap to implementing, managing, and leveraging the full potential of the powerful unified XDR + SIEM solution, starting with an overview of Zero Trust principles and the necessity of XDR + SIEM solutions in modern cybersecurity. From understanding concepts like EDR, MDR, and NDR and the benefits of the unified XDR + SIEM solution for SOC modernization to threat scenarios and response, you'll gain real-world insights and strategies for addressing security vulnerabilities. Additionally, the book will show you how to enhance Secure Score, outline implementation strategies and best practices, and emphasize the value of managed XDR and SIEM solutions. That's not all; you'll also find resources for staying updated in the dynamic cybersecurity landscape.By the end of this insightful guide, you'll have a comprehensive understanding of XDR, SIEM, and Microsoft's unified solution to elevate your overall security posture and protect your organization more effectively.What You Will Learn- Optimize your security posture by mastering Microsoft's robust and unified solution- Understand the synergy between Microsoft Defender's integrated tools and Sentinel SIEM and SOAR- Explore practical use cases and case studies to improve your security posture- See how Microsoft's XDR and SIEM proactively disrupt attacks, with examples- Implement XDR and SIEM, incorporating assessments and best practices- Discover the benefits of managed XDR and SOC services for enhanced protectionWho this book is forThis comprehensive guide is your key to unlocking the power of Microsoft's unified XDR and SIEM offering. Whether you're a cybersecurity pro, incident responder, SOC analyst, or simply curious about these technologies, this book has you covered.CISOs, IT leaders, and security professionals will gain actionable insights to evaluate and optimize their security architecture with Microsoft's integrated solution. This book will also assist modernization-minded organizations to maximize existing licenses for a more robust security posture.Table of Contents- Introduction to Zero Trust- Introduction to XDR & SIEM- Microsoft Unified XDR and SIEM Solution- Power of Investigation and SOC Experience with Microsoft XDR + SIEM- Defend attacks with Microsoft XDR + SIEM- Security Misconfigurations & Vulnerability Management- Assess and Improve Secure Score- XDR implementation Strategy, Roadmap and Best Practices- Managed XDR & SIEM- Useful Resources & References

The definitive guide to LLMs, from architectures, pretraining, and fine-tuning to Retrieval Augmented Generation (RAG), multimodal Generative AI, risks, and implementations with ChatGPT Plus with GPT-4, Hugging Face, and Vertex AIKey Features- Compare and contrast 20+ models (including GPT-4, BERT, and Llama 2) and multiple platforms and libraries to find the right solution for your project- Apply RAG with LLMs using customized texts and embeddings- Mitigate LLM risks, such as hallucinations, using moderation models and knowledge bases- Purchase of the print or Kindle book includes a free eBook in PDF formatBook DescriptionTransformers for Natural Language Processing and Computer Vision, Third Edition, explores Large Language Model (LLM) architectures, applications, and various platforms (Hugging Face, OpenAI, and Google Vertex AI) used for Natural Language Processing (NLP) and Computer Vision (CV).The book guides you through different transformer architectures to the latest Foundation Models and Generative AI. You'll pretrain and fine-tune LLMs and work through different use cases, from summarization to implementing question-answering systems with embedding-based search techniques. You will also learn the risks of LLMs, from hallucinations and memorization to privacy, and how to mitigate such risks using moderation models with rule and knowledge bases. You'll implement Retrieval Augmented Generation (RAG) with LLMs to improve the accuracy of your models and gain greater control over LLM outputs.Dive into generative vision transformers and multimodal model architectures and build applications, such as image and video-to-text classifiers. Go further by combining different models and platforms and learning about AI agent replication.This book provides you with an understanding of transformer architectures, pretraining, fine-tuning, LLM use cases, and best practices.What you will learn- Breakdown and understand the architectures of the Original Transformer, BERT, GPT models, T5, PaLM, ViT, CLIP, and DALL-E- Fine-tune BERT, GPT, and PaLM 2 models- Learn about different tokenizers and the best practices for preprocessing language data- Pretrain a RoBERTa model from scratch- Implement retrieval augmented generation and rules bases to mitigate hallucinations- Visualize transformer model activity for deeper insights using BertViz, LIME, and SHAP- Go in-depth into vision transformers with CLIP, DALL-E 2, DALL-E 3, and GPT-4VWho this book is forThis book is ideal for NLP and CV engineers, software developers, data scientists, machine learning engineers, and technical leaders looking to advance their LLMs and generative AI skills or explore the latest trends in the field.Knowledge of Python and machine learning concepts is required to fully understand the use cases and code examples. However, with examples using LLM user interfaces, prompt engineering, and no-code model building, this book is great for anyone curious about the AI revolution.Table of Contents- What are Transformers?- Getting Started with the Architecture of the Transformer Model- Emergent vs Downstream Tasks: The Unseen Depths of Transformers- Advancements in Translations with Google Trax, Google Translate, and Gemini- Diving into Fine-Tuning through BERT- Pretraining a Transformer from Scratch through RoBERTa- The Generative AI Revolution with ChatGPT- Fine-Tuning OpenAI GPT Models- Shattering the Black Box with Interpretable Tools- Investigating the Role of Tokenizers in Shaping Transformer Models(N.B. Please use the Read Sample option to see further chapters)

Cybersecurity Issues and Challenges in the Drone Industry is a comprehensive exploration of the critical cybersecurity problems faced by the rapidly expanding drone industry. With the widespread adoption of drones in military, commercial, and recreational sectors, the need to address cybersecurity concerns has become increasingly urgent. In this book, cybersecurity specialists collaborate to present a multifaceted approach to tackling the unique challenges posed by drones. They delve into essential topics such as establishing robust encryption and authentication systems, conducting regular vulnerability assessments, enhancing software security, advocating industry-wide standards and best practices, and educating drone users about the inherent cybersecurity risks. As drones, or unmanned aerial vehicles (UAVs), gain popularity and are deployed for various applications, ranging from aerial photography and surveillance to delivery services and infrastructure inspections, this book emphasizes the criticality of safeguarding the security, integrity, and privacy of drone systems and the data they handle. It highlights the growing vulnerability of drones to cybersecurity threats as these devices become increasingly connected and integrated into our everyday lives. This book is an invaluable resource for drone manufacturers, government agencies, regulators, cybersecurity professionals, and academia and research institutions invested in understanding and mitigating the cybersecurity risks in the drone industry.

I sistemi complessi sono agglomerati di individui, eventi e comportamenti che si basano su schemi di situazioni casuali che danno luogo a risultati futuristici quando vengono analizzati con strumenti informatici attraverso simulazioni al computer. La previsione di eventi non ancora accaduti non è mai stata così evidente come oggi, il che dimostra la sua importanza nell'ambiente attuale in cui viviamo. Tutta questa ricerca si basa sullo studio di modelli di eventi casuali che formano fatti e situazioni che possono o meno verificarsi con l'intervento umano.

La gestione di una rete di computer è un fattore molto importante, ma diventa molto complicata a causa dell'aumento dei nodi e dell'eterogeneità di software e hardware. Il protocollo SNMP ha contribuito notevolmente a questo compito. Tuttavia, il modello Client/Server, che utilizza la struttura manager-agente, causa molto traffico sulla rete a causa della sua forma strutturale, in quanto si basa sul polling, che può competere con il traffico di pacchetti, riducendo notevolmente le prestazioni della rete, in quanto i pacchetti di gestione competono con i pacchetti di dati. Alla luce di ciò, il modello basato sugli agenti mobili è emerso come un modo per ridurre al minimo questo trasferimento basato sul polling, in cui ogni nodo inoltra i risultati al successivo, che vengono raccolti da un agente e poi inoltrati al gestore, riducendo così la concorrenza tra i pacchetti e migliorando le prestazioni della rete in questione.

Slozhnye sistemy - äto skopleniq lüdej, sobytij i powedeniq, osnowannye na patternah sluchajnyh situacij, kotorye priwodqt k futuristicheskim rezul'tatam pri analize s pomosch'ü komp'üternyh instrumentow posredstwom komp'üternogo modelirowaniq. Predskazanie sobytij, kotorye esche ne proizoshli, nikogda ne bylo stol' ochewidnym, kak segodnq, chto dokazywaet ego wazhnost' w sowremennyh uslowiqh, w kotoryh my zhiwem. Vse äti issledowaniq osnowany na izuchenii zakonomernostej sluchajnyh sobytij, kotorye formiruüt fakty i situacii, kotorye mogut proizojti ili ne proizojti pri wmeshatel'stwe cheloweka.

Les systèmes complexes sont des agglomérations d'individus, d'événements et de comportements basés sur des schémas de situations aléatoires qui donnent lieu à des résultats futuristes lorsqu'ils sont analysés à l'aide d'outils informatiques dans le cadre de simulations informatiques. La prédiction d'événements qui ne se sont pas encore produits n'a jamais été aussi évidente qu'aujourd'hui, ce qui prouve son importance dans l'environnement actuel dans lequel nous vivons. Toutes ces recherches sont basées sur l'étude de modèles d'événements aléatoires qui forment des faits et des situations qui peuvent ou non se produire avec l'intervention de l'homme.

La gestion d'un réseau informatique est un facteur très important, mais elle devient très compliquée en raison de l'augmentation du nombre de n¿uds et de l'hétérogénéité des logiciels et du matériel. Le protocole SNMP a grandement facilité cette tâche. Mais le modèle Client/Serveur, qui utilise la structure gestionnaire-agent, cause beaucoup de trafic sur le réseau en raison de sa forme structurelle, car il est basé sur le polling, qui peut entrer en concurrence avec le trafic de paquets, réduisant considérablement les performances du réseau, car les paquets de gestion entrent en concurrence avec les paquets de données. Dans ce contexte, le modèle basé sur les agents mobiles est apparu comme un moyen de minimiser ce transfert basé sur l'interrogation, où chaque n¿ud transmet les résultats au suivant, qui sont collectés par un agent et ensuite transmis au gestionnaire, réduisant ainsi la concurrence entre les paquets et améliorant la performance du réseau en question.

Uprawlenie komp'üternoj set'ü - ochen' wazhnyj faktor, no on stanowitsq ochen' slozhnym iz-za uwelicheniq kolichestwa uzlow i neodnorodnosti programmnogo i apparatnogo obespecheniq. Odnako protokol SNMP znachitel'no oblegchil ätu zadachu. Odnako model' "klient-serwer", ispol'zuüschaq strukturu "menedzher-agent", iz-za swoej strukturnoj formy wyzywaet bol'shoj trafik w seti, tak kak osnowana na oprose, kotoryj mozhet konkurirowat' s paketnym trafikom, chto znachitel'no snizhaet proizwoditel'nost' seti, tak kak pakety uprawleniq konkuriruüt s paketami dannyh. V swqzi s ätim woznikla model' na osnowe mobil'nyh agentow kak sposob minimizacii ätoj peredachi na osnowe oprosa, kogda kazhdyj uzel peresylaet rezul'taty sleduüschemu, kotorye sobiraütsq agentom i zatem peresylaütsq menedzheru, chto snizhaet konkurenciü mezhdu paketami i powyshaet proizwoditel'nost' rassmatriwaemoj seti.

Komplexe Systeme sind Ansammlungen von Individuen, Ereignissen und Verhaltensweisen, die auf Mustern von Zufallssituationen beruhen, die bei der Analyse mit Hilfe von Computerwerkzeugen durch Computersimulationen zu zukunftsweisenden Ergebnissen führen. Die Vorhersage von Ereignissen, die noch nicht eingetreten sind, war noch nie so offensichtlich wie heute, was beweist, wie wichtig sie in unserem heutigen Umfeld ist. Alle diese Forschungen basieren auf der Untersuchung von Mustern zufälliger Ereignisse, die Fakten und Situationen bilden, die durch menschliches Eingreifen eintreten können oder auch nicht.

Die Verwaltung eines Computernetzes ist ein sehr wichtiger Faktor, wird aber durch die Zunahme der Knoten und die Heterogenität von Software und Hardware sehr kompliziert. Das SNMP-Protokoll hat diese Aufgabe jedoch erheblich erleichtert. Das Client/Server-Modell, das die Manager-Agent-Struktur verwendet, verursacht jedoch aufgrund seiner strukturellen Form eine Menge Datenverkehr im Netz, da es auf Abfragen basiert, die mit dem Paketverkehr konkurrieren können, was die Leistung des Netzes erheblich beeinträchtigt, da Verwaltungspakete mit Datenpaketen konkurrieren. In Anbetracht dessen hat sich das auf mobilen Agenten basierende Modell als eine Möglichkeit herauskristallisiert, diese Übertragung auf der Grundlage von Polling zu minimieren, bei der jeder Knoten die Ergebnisse an den nächsten weiterleitet, die von einem Agenten gesammelt und dann an den Manager weitergeleitet werden, wodurch der Wettbewerb zwischen den Paketen verringert und die Leistung des betreffenden Netzes verbessert wird.

Los sistemas complejos son aglomeraciones de individuos, acontecimientos y comportamientos que se basan en patrones de situaciones aleatorias que dan lugar a resultados futuristas cuando se analizan con herramientas informáticas mediante simulaciones por ordenador. La predicción de acontecimientos que aún no han sucedido nunca ha sido tan evidente como hoy, lo que demuestra su importancia en el entorno actual en el que vivimos. Todas estas investigaciones se basan en el estudio de patrones de sucesos aleatorios que conforman hechos y situaciones que pueden suceder o no con la intervención humana.

Der New York Times- Bestseller - Michael Harriot, gefeierter Kommentator, Kolumnist und Kunstkritiker demontiert mit viel Schwarzem Humor die Geschichte der USA als eine ziemlich weißgewaschene und erzählt sie neu Der Gründungsmythos der USA beruht auf den immer gleichen Erzählungen: Die Geschichte der Pilger auf der Mayflower, die eine neue Nation gründen. Die Geschichte von George Washingtons Kirschbaum und Abraham Lincolns Blockhaus. Die Geschichte breitschultriger afrikanischer Sklaven, die sich mit ihren Gospels auf den Lippen spontan auf die Tabakplantagen und Baumwollfelder gebeamt hatten. Die Geschichte von Thomas Jefferson und seiner Unabhängigkeitserklärung von 1776. Es sind gebleichte Triumphe. Geschichten, die bis heute unsere Geschichtsbücher bestimmen - geschrieben und rezipiert von vor allem weißen Männern, die ihre Sichtweise in den Vordergrund stellen. Michael Harriot zeigt die berühmten weißen Männer in ihrer nicht ganz so weißen Weste: Von den ersten achtzehn Präsidenten der Vereinigten Staaten waren zwölf Sklavenhalter, acht von ihnen sogar während ihrer Amtszeit. Thomas Jefferson, Verfasser der berühmten Worte »alle Menschen sind gleich beschaffen« (»all men are created equal«) besaß Zeit seines Lebens sogar über sechshundert. Ein präsidentieller Rekord. Mit bissigem Humor und vielen Fakten untergräbt Michael Harriot die vermeintlich weißen Wahrheiten mit den bisher wenig bekannten Erfahrungen, Erlebnissen und Sichtweisen Schwarzer Amerikaner. Von den Afroamerikanern, die bereits vor 1619 in die sogenannte Neue Welt kamen, bis hin zu dem nicht zu versklavenden Banditen, der Amerikas erste Polizeikräfte inspirierte, bietet Harriots Version das längst überfällige Korrektiv der Geschichte. Lange haben wir uns geweigert, anzuerkennen, dass die amerikanische Geschichte eine weiße Geschichte ist . Diese ist es nicht. Diese Geschichte ist Black As F***. »Man könnte sogar sagen, dass die Abwertung und Auslöschung Schwarzer Erfahrung so amerikanisch ist wie Apple Pie.« »So hätten wir uns den Geschichtsunterricht in der Schule gewünscht. Auf halber Strecke merkt man, dass es gar kein Buch über die Geschichte der Schwarzen in Amerika ist, sondern darüber, wie verdammt Schwarz die amerikanische Geschichte ist.« Pharell Williams, Produzent, Musiker und Grammy-Gewinner (u. a. »Happy«) »Michael Harriot hat's getan. Sein Buch ruft die komplette Bandbreite an Emotionen hervor: Lachen. Wut. Traurigkeit. Liebe (zum Schwarzen Widerstand). Hass (auf Anti-Schwarzsein). Mehr Lachen. Kontinuierliches Denken, Erkennen von Zusammenhängen, Verstehen und Entdecken.« Ibram X. Kendi, Amerikas bekanntester Rassismusforscher und u. a. Autor von »Gebrandmarkt«

Rebellen im Reich der Feen Eliane regiert ihren ersten Sommer als Königin. Doch die Rebellen, die im Frühling versucht haben, die böse Kaiserin an die Macht zu bringen, sorgen immer noch für Aufruhr im Reich der Feen. Außerdem macht sich die Trockenheit des Sommers in einigen Teilen des Landes besonders stark bemerkbar und Elianes gut gemeinte Entscheidungen haben nicht immer die beabsichtigte Wirkung. Zu reagieren ist gar nicht so einfach, und zunehmend zweifelt die junge Feenkönigin daran, ob sie die Zukunft ihres Volkes im Einklang mit den Jahreszeiten alleine bestimmen sollte. Doch zum Glück ist sie nicht ganz alleine, und gemeinsam mit ihrer Freundin Rosa hat sie schon so manches Abenteuer gemeistert. Die beiden machen sich auf die Suche nach den uralten magischen Steinen helfen, die ihnen helfen könnten, Frieden ins Reich der Feen zu bringen - oder es ins Chaos zu stürzen. Abenteuer, Freundschaft und Bewusstsein für Klimaschutz für Kinder ab 10 Jahren - Band 2 der spannenden Feen-Fantasy

Alles Wissenswerte über Creeper, Zombies & Co. Das Lexikon der Mobs bietet alles, was es über die siebenundneunzig Mobs in Minecraft zu wissen gibt. Sieben Experten stellen mit spannenden Geschichten im Gepäck ihre Erfahrungen im Spiel vor und nehmen dich mit auf eine Reise durch die gesamte Oberwelt. Und auch im Nether und im Ende gibt es gefährliche Monster zu entdecken. Finde heraus, wie du eine Schießerei mit Skeletten überlebst, wie du mit Delphinen zu Schätzen tief unter Wasser hinabtauchst oder ob du ein Treffen mit dem Enderdrachen riskieren solltest - dann bist du perfekt vorbereitet, um dich selbst auf ins Abenteuer zu begeben. Offizielles Lexikon von den Machern des Spiels mit vielen Tipps und Tricks für neue und erfahrene Fans des Spiels