Böcker utgivna av BPB Publications

DESCRIPTIONAdvanced Malware Analysis and Intelligence teaches you how to analyze malware like a pro. Using static and dynamic techniques, you will understand how malware works, its intent, and its impact. The book covers key tools and reverse engineering concepts, helping you break down even the most complex malware.This book is a comprehensive and practical guide to understanding and analyzing advanced malware threats. The book explores how malware is created, evolves to bypass modern defenses, and can be effectively analyzed using both foundational and advanced techniques. Covering key areas such as static and dynamic analysis, reverse engineering, malware campaign tracking, and threat intelligence, this book provides step-by-step methods to uncover malicious activities, identify IOCs, and disrupt malware operations. Readers will also gain insights into evasion techniques employed by malware authors and learn advanced defense strategies. It explores emerging trends, including AI and advanced attack techniques, helping readers stay prepared for future cybersecurity challenges.By the end of the book, you will have acquired the skills to proactively identify emerging threats, fortify network defenses, and develop effective incident response strategies to safeguard critical systems and data in an ever-changing digital landscape.WHAT YOU WILL LEARN¿ Gain a complete understanding of malware, its behavior, and how to analyze it using static and dynamic techniques.¿ Reverse engineering malware to understand its code and functionality.¿ Identifying and tracking malware campaigns to attribute threat actors.¿ Identify and counter advanced evasion techniques while utilizing threat intelligence to enhance defense and detection strategies.¿ Detecting and mitigating evasion techniques used by advanced malware.WHO THIS BOOK IS FORThis book is tailored for cybersecurity professionals, malware analysts, students, and incident response teams. Before reading this book, readers should have a basic understanding of operating systems, networking concepts, any scripting language, and cybersecurity fundamentals.

DESCRIPTIONStatistics is a powerful tool for data analysis, visualization, and inference. Python is a popular programming language that offers a rich set of libraries and frameworks for statistical computing. Together, they can help you solve real-world problems and make informed decisions based on data. This book teaches you how to use Python to implement statistical concepts and techniques in a practical and effective way. You will also learn how to perform data science and analysis to generate insights, patterns, and trends.This book introduces the basics of statistics, such as descriptive and inferential statistics, ML, probability distributions, hypothesis testing, and confidence intervals. It also covers advanced topics such as regression analysis, linear algebra, statistical tests, time series, survival, and correlation analysis. You will learn how to identify patterns, interpret data, and make data-driven decisions. The book emphasizes practical learning with examples, exercises, and code snippets using popular Python libraries like NumPy, Pandas, Matplotlib, Seaborn, and SciPy to perform various statistical tasks.By the end of this book, you will have a solid foundation in statistics and Python programming. You will be able to explore, analyze, and visualize data using Python. You will also be able to perform various statistical tests and interpret the results.WHAT YOU WILL LEARN¿ Master data manipulation, cleaning, and visualization techniques using Python.¿ Apply core statistical methods to analyze real-world datasets.¿ Build and evaluate statistical models for regression, classification, and clustering.¿ Interpret and communicate insights derived from statistical analyses effectively.¿ Explore advanced statistical techniques like time series and survival analysis.WHO THIS BOOK IS FORThis book is ideal for data scientists, ML engineers, statisticians, Python practitioners, researchers, and anyone who works with data and statistics.

DESCRIPTIONGenerative AI is changing the way we think about creativity and problem-solving. This book is your go-to guide for understanding and working with this exciting technology.This book offers a clear introduction to generative AI, starting with basics like machine learning and deep learning. It explains key models, including GANs and VAEs, breaking down their architectures and training methods. You will discover how Transformer models like GPT have transformed natural language processing and enabled advancements in language generation. The book explores practical applications such as image synthesis, style transfer, and text generation, showing how generative AI merges technology with creativity. Advanced topics like reinforcement learning, AI ethics, and bias are also covered. Practical tips for creating your own generative AI models, along with insights into the future of this groundbreaking field, making it an essential resource for AI enthusiasts and professionals.By the end of this book, you will have a firm grasp of generative AI concepts and practical skills to get you started. You will be well-prepared to use cloud platforms like AWS, Azure, and GCP to build and launch powerful generative AI projects. From creating realistic images to crafting natural text, you will explore hands-on examples while tackling important ethical questions. This book gives you the skills and confidence to explore the limitless potential of generative AI.WHAT YOU WILL LEARN¿ Build foundational knowledge of generative AI principles and models.¿ Apply machine learning and deep learning for creative content generation.¿ Leverage GANs, VAEs, and Transformer models in real-world scenarios.¿ Master cloud tools for scalable generative AI development.¿ Address ethical challenges and implement responsible AI practices.¿ Explore advanced applications and future directions of generative AI.WHO THIS BOOK IS FORThis book is designed for data scientists, machine learning engineers, software developers, cloud professionals, educators, students, and creative professionals.

DESCRIPTIONMastering Neural Network Computer Vision with TensorFlow and Keras provides a comprehensive guide to using TensorFlow and Keras for computer vision applications. The book enables readers to develop and exercise the skills needed to use sophisticated pre-trained computer vision models, build simple and more advanced neural network models, and optimize their performance.The different chapters of the book cover a comprehensive range of topics in computer vision and deep learning. The first chapter provides a theoretical introduction to computer vision and deep learning, and the second one provides an overview of TensorFlow and its capabilities. The subsequent chapters cover specific applications of neural networks in computer vision, such as image classification, image segmentation, and object detection, and how to tap into the power of transfer learning and pre-trained models to address those use cases. Finally, the remaining chapters cover how to design your own neural network, gather a proper dataset and train your model efficiently. They also cover image generation and ethical considerations around computer vision.By the end of this book, readers will have a strong understanding of the principles of deep learning and computer vision, as well as the skills needed to build advanced neural network models using TensorFlow.WHAT YOU WILL LEARN¿ Understand essential deep learning concepts and architectures specifically designed for modern computer vision applications.¿ Build practical expertise with Tensorflow and Keras while implementing pre-trained models for vision tasks.¿ Learn to fine-tune existing models and design new architectures for specific vision challenges.¿ Master techniques to improve model efficiency, training speed, and overall performance in real applications.¿ They will know how diffusion-based models work and how to use some of the most popular ones, like DALL-E or Stable Diffusion.WHO THIS BOOK IS FORThis book is for current or aspiring deep tech professionals, students, and anyone who wishes to understand the rewarding field of computer vision. More specifically, it will also have a great impact on computer vision engineers, robotics, image processing, and video processing engineers who are willing to learn how to use neural networks to boost their performance and results.

DESCRIPTIONThis book teaches you to draw insights from your data. In today's data-driven business landscape, making informed decisions requires effective data analysis. This book guides you through the steps to import, structure, and visualize your data in R, and apply statistical and ML algorithms to drive better insights.This book offers a thorough introduction to data science, starting with R programming basics and advancing to ML and data visualization. Learn to clean, explore, and transform data using tools like dplyr. Key statistical concepts like probability, hypothesis testing, and modeling are covered, providing a foundation for data-driven decisions. Discover supervised and unsupervised ML techniques, feature engineering, and model evaluation. The book also provides career guidance in data science, including skill-building tips and job search strategies, equipping you to excel in this growing field.By the end of this book, you will be able to confidently use R to prepare data for analysis and apply ML algorithms to make predictions and drive business decisions.KEY FEATURES¿ Master R for effective data analysis and ML.¿ Analyze data, identify patterns, and drive informed decision-making.¿ Learn by doing hands-on R codes and applying ML techniques.WHAT YOU WILL LEARN¿ Use R to clean, analyze, and visualize data effectively.¿ Apply statistical techniques to find patterns and trends in data.¿ Understand and implement key ML algorithms step-by-step.¿ Data visualization techniques using ggplot2 to create informative visualizations.¿ Strong foundation in statistical concepts, including probability theory, hypothesis testing, and statistical modeling.WHO THIS BOOK IS FORThis book is ideal for individuals with a basic understanding of programming and statistics who aspire to enter the field of data science. Professionals such as data analysts, software engineers, and researchers will find this book particularly valuable as it provides a practical approach to leveraging data for informed decision-making.

DESCRIPTIONBeginning with Tableau Cloud is the essential toolkit for crafting intuitive and high-performance visuals over the web. This book provides a practical understanding of building, managing, and deploying workbooks on Tableau Cloud.This book explores Tableau's cloud platform, starting with the basics of data visualization and connecting to diverse sources, including live connections and efficient data extracts. It covers creating charts from simple bar graphs to advanced visualizations like dual-axis charts and LOD calculations. Readers will learn to enhance dashboards with interactive features like parameters, actions, and animations. The book also focuses on managing content, sharing dashboards, setting up alerts, handling site administration, user management, and data security. Practical challenges such as troubleshooting connectivity, refresh issues, and optimizing performance are addressed. Real-world projects included in the chapters will help readers apply their skills to analyze complex datasets, craft engaging dashboards, and effectively communicate data insights.This book helps BI developers to understand their roles and responsibilities. It also helps to leverage their Tableau capabilities to become Cloud server site administrators. Furthermore, you will gain the skills to effectively manage, share, and collaborate on your work, driving data-driven decision-making within your organization.WHAT YOU WILL LEARN¿ Master Tableau Cloud functionalities and services.¿ Build secure, interactive, and intuitive dashboards and stories on the cloud.¿ Deploy and manage data sources and workbooks on the web.¿ Manage published content, learn how to secure data, and troubleshoot frequently occurring issues on the Cloud.¿ Managing user security and privileges.WHO THIS BOOK IS FORThis book is for visualization experts, BI professionals, data professionals, non-technical business users, data analysts, BI analysts, or students aspiring to become Tableau site administrators. It is geared towards developers and analysts curating content on Tableau Cloud.

DESCRIPTIONThis book is a workshop to create software using AI. A reader will be taken through a series of requirements and create a practical API from scratch. AI is without a doubt a productivity boost, and our goal is to help you maximize the boost by writing prompts effectively to generate, refactor, test, and review code.This book is also a modern take on software design fundamentals. To be able to scrutinize AI-generated code and to be able to guide AI effectively to better results, one should understand the theory behind software design. It starts with basics like clean function design and object-oriented principles, then advances to SOLID principles, design patterns, and Onion architecture. Readers will learn essential testing methods, including unit, integration, and acceptance tests using BDD and Specflow. The guide covers API development, focusing on security, validation, error handling, and external system integration. It also explains CI/CD pipelines using Azure DevOps, including build and deployment pipelines with YAML configurations.Lastly, this book teaches us to embrace the changes in software requirements. The end goal is to teach a reader how to implement changes in software with minimum change to existing lines of code.You will be well-equipped to leverage AI as a valuable asset in your software development toolbox.WHAT YOU WILL LEARN¿ The fundamentals of software design like KISS, OOP, SOLID, and key design Patterns.¿ Use Effective prompt engineering for generating code, refactoring, testing, and reviewing.¿ Code review both for human and AI-generated code.¿ Design which minimizes changes when new requirements are introduced.¿ Build .NET REST Web API with tests.¿ Build CI/CD pipelines to deploy to Azure.WHO THIS BOOK IS FORThis book is intended for software developers, aspiring programmers, and students in computer science or related fields who have a basic understanding of programming concepts and are eager to deepen their knowledge of software design principles and best practices.

DESCRIPTIONHands-on Splunk on AWS is a practical tutorial for professionals who wish to set up, manage, and analyze data with Splunk on AWS. This practical guide capitalizes on the scalability and flexibility of Amazon Web Services (AWS) to streamline your Splunk deployment.This book is a complete guide to Splunk, a powerful tool for analyzing and visualizing machine-generated data. It explains Splunk's architecture, components, and data flow, helping you set up, configure, and index data effectively. Learn to write efficient Splunk Processing Language (SPL) queries, create detailed visualizations, and optimize searches for deeper insights. Discover advanced topics like clustering and integrating Splunk into modern DevOps practices and cloud-native environments. The book also shares best practices for administration, troubleshooting, and security.By the end of this guide, readers will be confident in utilizing Splunk on AWS to make data-driven decisions. Whether you want to improve your data analysis or use AWS for Splunk, this book will teach you the skills and insights you need in today's data-driven world.KEY FEATURES¿ Understand Splunk's search language to query, analyze, and visualize data.¿ Create interactive dashboards and reports to communicate insights effectively.¿ Integrate Splunk with modern DevOps practices to improve monitoring and troubleshooting.WHAT YOU WILL LEARN¿ How to deploy and configure Splunk effectively on AWS.¿ Key concepts and tools in data onboarding and indexing.¿ Mastery of the Splunk Processing Language (SPL) for data queries.¿ Techniques for creating and managing interactive dashboards.¿ Integration of Splunk with Kubernetes and CI/CD pipelines.¿ Methods for applying machine learning in data analysis with Splunk.WHO THIS BOOK IS FORThis book is for IT professionals, data analysts, Splunk administrators, and cloud enthusiasts to improve their understanding of Splunk on AWS and extract valuable insights from their data.

DESCRIPTIONThe book provides a comprehensive exploration of Java security and penetration testing, starting with foundational topics such as secure coding practices and the OWASP Top 10 for web applications. The early chapters introduce penetration testing methodologies, including Java web application-specific mapping and reconnaissance techniques. The gathering of information through OSINT and advanced search techniques is highlighted, laying the crucial groundwork for testing. Proxy tools like Burp Suite and OWASP Zap are shown, offering insights into their configurations and capabilities for web application testing.Each chapter does a deep dive into specific vulnerabilities and attack vectors associated with Java web and mobile applications. Key topics include SQL injection, cross-site scripting (XSS), authentication flaws, and session management issues. Each chapter supplies background information, testing examples, and practical secure coding advice to prevent these vulnerabilities. There is a distinct focus on hands-on testing methodologies, which prepares readers for real-world security challenges.By the end of this book, you will be a confident Java security champion. You will understand how to exploit vulnerabilities to mimic real-world attacks, enabling you to proactively patch weaknesses before malicious actors can exploit them.WHAT YOU WILL LEARN¿ Study the OWASP Top 10 and penetration testing methods.¿ Gain secure coding and testing techniques for vulnerabilities like XSS and CORS.¿ Find out about authentication, cookie management, and secure session practices.¿ Master access control and authorization testing, including IDOR and privilege escalation.¿ Discover Android app security and tools for SAST, DAST, and exploitation.WHO THIS BOOK IS FORThis book is for Java developers, software developers, application developers, quality engineers, software testing teams, and security analysts. Prior knowledge of Java is required. Some application security knowledge is helpful.

DESCRIPTIONThis book "Artificial Intelligence and Financial Security" explores the transformative power of AI in enhancing and safeguarding financial systems. This comprehensive guide looks into AI-driven solutions for fraud detection, risk management, regulatory compliance, and market forecasting.With detailed case studies, actionable insights, and expert analyses, the book equips the readers to tackle emerging challenges in financial security. It provides a deep dive into cutting-edge technologies like ML, blockchain, and AI-powered cybersecurity, while highlighting the critical importance of ethical considerations and compliance with financial regulations. Each chapter is thoughtfully structured to guide readers from foundational concepts to practical strategies and insights into future trends in AI-driven finance.By the end of this book, you will be well-positioned to understand how AI is shaping the future of financial security. You will possess the knowledge to make informed financial decisions and navigate the increasingly AI-driven financial landscape with confidence.WHAT YOU WILL LEARN¿ Understanding the role of AI in securing and optimizing financial systems.¿ Detect fraud and manage risks using AI-driven strategies.¿ Apply ML for predictive analytics and anomaly detection.¿ Integrate blockchain and AI for enhanced financial security.¿ Navigate ethical and regulatory challenges in AI implementation.¿ Forecast trends and prepare for AI-driven financial innovation.WHO THIS BOOK IS FORThis book is for financial professionals, AI practitioners, researchers, and policymakers seeking to understand and apply AI in financial security. A basic understanding of finance, technology, or AI concepts is helpful but not mandatory, as the book provides foundational explanations alongside advanced insights.

DESCRIPTIONDigital Technology 360° is a comprehensive guide to understanding the fundamentals and implications of today's most transformative technologies. From foundational innovations like cloud computing, artificial intelligence, and big data to emerging fields like the IoT, 5G/6G, the metaverse, and quantum computing, this book offers an unparalleled exploration of digital technologies shaping the world.Going beyond the technical aspects, the book connects technology with its broader societal impacts by examining the roles of industry, governments, NGOs, and United Nations agencies in fostering innovation, setting standards, and addressing ethical considerations. It explores opportunities and risks, offering strategic insights into navigating challenges such as AI safety, data privacy, and technology governance. Readers will gain the tools to understand trends, prepare for future developments, and make informed decisions about adopting and utilizing digital technologies in ways that align with both business goals and global ethical standards.By the end of this book, you will have a well-rounded understanding of digital technology, helping you to make informed decisions in a world increasingly driven by technology. Digital Technology 360° provides a well-rounded foundation to navigate the digital age effectively.WHAT YOU WILL LEARN¿ Grasp the basics of digital technologies, including AI, cloud computing, IoT, 5G/6G, quantum computing, and the metaverse.¿ Understand the risks and challenges of developing and using digital technology.¿ Develop strategic thinking to balance business benefits with safety and ethical considerations.¿ Explore the global standards and governance landscape for digital technology adoption.¿ Learn how leaders can foster international collaboration in adopting digital advancements.WHO THIS BOOK IS FORWhether you are a policymaker, engineer, IT professional, business manager, or simply curious about digital applications, this book equips you to engage with the technologies driving the digital revolution.

DESCRIPTIONAngular is a popular JavaScript framework that empowers developers to create single-page applications (SPAs) with ease. This comprehensive guide is designed to equip you with the skills and knowledge to become a proficient Angular developer, even if you are starting from scratch.This book offers a step-by-step guide to mastering Angular development. It starts with setting up your environment, using Angular CLI for efficient project management, and creating reusable components that form the core of any Angular app. You will learn data binding to connect data with your user interface and routing to guide users through your app's sections. The book covers TypeScript basics, Angular's primary language, and component lifecycle hooks for managing behavior at different stages. Advanced topics include handling user input with reactive forms, testing for quality assurance, and deploying your application effectively. Additionally, it covers styling to create attractive designs and accessibility practices to ensure your applications are usable for everyone.By the end of this masterclass, you will be well-equipped to confidently build modern, interactive, and user-friendly web applications using the power of Angular.WHAT YOU WILL LEARN¿ Optimize Angular applications for performance and responsiveness.¿ Utilize advanced Angular features like lazy loading and preloading.¿ Optimize applications using change detection strategies and performance profiling.¿ Debug production issues effectively with monitoring, telemetry tools, and error-handling mechanisms.¿ Implement internationalization (i18n) for multilingual applications.¿ Explore component lifecycle and its management.WHO THIS BOOK IS FORThis book is ideal for aspiring and intermediate web developers, front-end engineers, and anyone interested in building dynamic web applications. Prior experience to basic JavaScript is recommended, but no prior knowledge of Angular is required.

DESCRIPTIONGo, a modern and efficient programming language, is rapidly gaining popularity for building robust and scalable applications. This book, Go Lang in Depth, instills you with the knowledge and skills to master Go, from its fundamental building blocks to advanced concepts.This Go programming book provides a detailed guide, starting from basic syntax and data structures to advanced concepts like concurrency and error handling. It teaches you how to build applications, including console apps, REST APIs, and web apps using popular frameworks like Gin and Beego. You will also explore creating real-world projects, such as a CRM system, and understand advanced topics like dependency injection, SOLID principles, and Docker containerization. The book covers performance optimization with profiling and benchmarking, ensures application security with authentication and cryptography, and explains design patterns and best practices for building scalable, secure web applications.By the end of this book, you will be equipped to write clean, concurrent, and performant Go code. You will understand how to design and implement complex functionalities, leverage Go's powerful features effectively, and tackle real-world programming challenges.KEY FEATURES¿ From beginner to advanced, this book covers all aspects of Go programming.¿ Learn by implementing practical examples and real-world projects.WHAT YOU WILL LEARN¿ Practical approach with hands-on exercises, real-world examples, and practical projects.¿ Gain a thorough understanding of Go's core concepts, including concurrency, error handling, and testing.¿ Learn to containerize Go applications with Docker and deploy them to production environments.¿ Implement security measures and optimize the performance of your Go applications.WHO THIS BOOK IS FORWhether you are a software engineer, data scientist, or system administrator, this book will help you harness the power of Go to build efficient, scalable, and reliable applications. No prior knowledge of Go is required, but a basic understanding of programming concepts will be beneficial.

DESCRIPTIONThis book is a practical guide to mastering Terraform and IaC, helping readers build, manage, and scale modern infrastructure.It introduces setting up Terraform environments, mastering HashiCorp Configuration Language (HCL), and managing infrastructure state effectively. Learn to use Terraform providers for cloud platforms, define resources, and use variables and outputs for dynamic setups. Advanced topics include reusable modules, CI/CD integration, performance tuning, and security best practices. It also explores Terraform Cloud and Enterprise, covering remote state, VCS integration, team management, and Sentinel policies for enterprise-level control, making it a complete resource for mastering Terraform and IaC.By the end of this book, you will be well-equipped to manage your cloud infrastructure with confidence. You will gain expertise in configuration management, security best practices, and even explore features of Terraform Cloud and Enterprise for enhanced collaboration and team management.KEY FEATURES¿ Guide to Terraform and infrastructure as code (IaC).¿ Practical Terraform examples and solutions.¿ Master advanced ways to manage infrastructure using Terraform.WHAT YOU WILL LEARN¿ Set up Terraform and create reusable infrastructure configurations.¿ Manage cloud environments with advanced orchestration techniques.¿ Securely handle sensitive data and optimize infrastructure performance.¿ Test and validate configurations for reliability and compliance.¿ Anticipate trends like AI integration and multi-cloud strategies.WHO THIS BOOK IS FORThis book is for developers, system administrators, and DevOps professionals looking to start using Terraform and IaC.

DESCRIPTIONThis book prepares you with the knowledge and skills to confidently excel in the exciting world of machine learning (ML) interviews and launch a successful career in this dynamic field.This book offers a collection of curated questions and answers to help readers understand key ML concepts, including data processing, classification, regression, clustering, dimensionality reduction, time series, and natural language processing (NLP). While not exhaustive, it focuses on critical topics and common questions often encountered in interviews. The chapters highlight essential concepts without a strict order of importance, reflecting the informal nature of ML interviews. Alongside theoretical knowledge, the book emphasizes the importance of coding and real-world application for a deeper understanding. Practical exercises, coding projects, and continuous learning are crucial to mastering ML concepts.By mastering the concepts and question-answer formats presented in this book, you will be well-prepared to tackle technical interview challenges and confidently showcase your ML expertise. This guide will help you achieve your career goals in the exciting field of ML.WHAT YOU WILL LEARN¿ Understand core data concepts for ML.¿ Master classification and regression algorithms.¿ Learn clustering and dimensionality reduction techniques.¿ Analyze and forecast time-dependent data with time series analysis.¿ Gain NLP proficiency and understand human language with techniques like tokenization, stemming, lemmatization, and advanced language models.WHO THIS BOOK IS FORThis book can be used by an interviewee, interviewer, ML professionals who want to learn the interview structure, and ML practitioners who want to refresh their memory and use this book as a reference guide. Managerial and non-technical people can use this book to learn ML in unique ways through a question-answer format.

DESCRIPTIONThe purpose of the book Web Automation Testing Using Playwright is to teach you how to use Playwright to automate your web testing. Playwright, a powerful automation tool developed by Microsoft, is a modern web automation framework that is fast, reliable, and easy to use.This book begins by introducing automation testing, its benefits, and Playwright, covering setup, scripting, and Playwright's architecture. It guides you through creating frameworks, selector strategies, and handling complex web elements like shadow DOM and iframes. Explore Playwright features such as Codegen, Inspector, UI mode, debugging with Trace Viewer, and generating detailed reports. Learn advanced techniques like building frameworks using Page Object Model (POM), integrating Cucumber/BDD, API testing, HTTP request interception, and accessibility and visual testing. Additionally, the book explores test execution in CI/CD tools, parallel testing, AI-driven test automation, leveraging generative AI like ChatGPT, and future trends in test automation.By the end of this book, you will be a web automation expert, writing efficient tests that validate web app functionality. Automate complex scenarios, handle edge cases, and leverage AI for intelligent testing.WHAT YOU WILL LEARN¿ Writing testing scripts for end-to-end, functional, API, accessibility, and visual tests with Playwright.¿ Mastering UI elements like alerts, tabs, drag-and-drop, iframes, and shadow DOM handling.¿ Debugging effectively using Playwright features like Codegen, Inspector, UI mode, and Trace Viewer.¿ Implementing Cucumber/BDD, Page Object Model (POM), and CI/CD pipeline integration with Playwright.¿ Leveraging AI tools for test automation, including script creation, debugging, and understanding generative AI like ChatGPT.WHO THIS BOOK IS FORThe target audience for this book is test automation engineers, web developers, product owners, and anyone who wants to learn about tool Playwright and test their application from scratch to the end of the applications.

DESCRIPTIONExplore the world of generative AI, a technology capable of creating new data that closely resembles reality. This book covers the fundamentals and advances through cutting-edge techniques. It also clarifies complex concepts, guiding you through the essentials of deep learning, neural networks, and the exciting world of generative models, like GANs, VAEs, Transformers, etc.This book introduces deep learning, machine learning, and neural networks as the foundation of generative models, covering types like GANs and VAEs, diffusion models, and other advanced architectures. It explains their structure, training methods, and applications across various fields. It discusses ethical considerations, responsible development, and future trends in generative AI. It concludes by highlighting how generative AI can be used creatively, transforming fields like art and pushing the boundaries of human creativity, while also addressing the challenges of using these technologies responsibly.This book provides the tools and knowledge needed to leverage generative AI in real-world applications. By the time you complete it, you will have a solid foundation and the confidence to explore the frontiers of AI.KEY FEATURES¿ Comprehensive guide to mastering generative AI and deep learning basics.¿ Covers text, audio, and video generation with practical examples.¿ Insights into emerging trends and potential advancements in the field.WHAT YOU WILL LEARN¿ Understand the fundamentals of deep learning and neural networks.¿ Master generative models like GANs, VAEs, and Transformers.¿ Implement AI techniques for text, audio, and video creation.¿ Apply generative AI in real-world scenarios and applications.¿ Navigate ethical challenges and explore the future of AI.WHO THIS BOOK IS FORThis book is ideal for AI enthusiasts, developers, and professionals with a basic understanding of Python programming and machine learning.

DESCRIPTIONGenerative AI for Financial Services is a book targeted at any AI practitioner who wants to understand how generative AI works on a fundamental level and extend that learning to risks, challenges, and opportunities in regulated industries like financial services.This book explores generative AI and its applications in financial services. It starts by explaining key concepts, differences from traditional AI, and the generative AI lifecycle. Readers learn about foundation models, transfer learning, and implementation strategies, including fine-tuning and training models. Practical use cases like improving customer experiences, automating ESG analysis, and optimizing contact centers are covered. The book also addresses challenges like model bias, ethics, and compliance while focusing on building trustworthy AI with fairness and accountability. Finally, it highlights MLOps and FMOps for efficient AI model deployment and management in production environments.By the end of this book, you will be well-equipped to navigate the exciting world of generative AI and confidently apply its transformative potential within the financial services landscape.KEY FEATURES¿ Evolve from a generative AI enthusiast to an advanced practitioner in generative AI.¿ Learn effective ways of building generative AI solutions for financial services.¿ Become familiar with the upcoming trends in generative AI space.WHAT YOU WILL LEARN¿ Learn about popular use-cases, challenges, risks in financial services, and how to overcome those.¿ Learn how to launch and scale generative AI applications in regulated environments like financial services, expanding from tens to thousands of use cases.¿ Understand the operational aspects of AI, including MLOps and FMOps.¿ Address challenges and ethical considerations in AI implementation.WHO THIS BOOK IS FORThis book is suitable for generative AI engineers, prompt engineers, ML engineers, data scientists, AI/ML, and technical leaders in financial services.

DESCRIPTIONPostgreSQL, a robust and versatile relational database management system (RDBMS), is gaining immense popularity due to its reliability, scalability, and rich feature set. This book is your indispensable companion to mastering PostgreSQL, helping you become a great PostgreSQL developer and create amazing database-driven applications.This book provides a thorough introduction to PostgreSQL, covering the fundamentals of database creation and management to advanced topics like data modeling, query optimization, and performance tuning. Explore PostgreSQL's powerful features, including multi-version concurrency control (MVCC), data types, constraints, and indexing. Learn how to install, configure, and apply PostgreSQL in real-world scenarios. You will also develop essential SQL skills to manipulate and analyze data, design efficient schemas with normalization, and use stored procedures and triggers to automate tasks effectively.By the end of this book, you will have a solid understanding of PostgreSQL's core concepts and best practices. You will be able to create complex database structures, write efficient SQL queries, optimize database performance, and implement robust data management strategies.KEY FEATURES¿ A comprehensive overview of PostgreSQL, covering all essential topics from database fundamentals to advanced features.¿ Relates concepts to real-world scenarios, helping you understand how to apply PostgreSQL in practical applications.¿ Provides step-by-step instructions and guidance, making it easy to follow along and learn effectively. It also includes MCQs in each chapter to engage the readers.WHAT YOU WILL LEARN¿ Database fundamentals like creation, structure, data types, and constraints.¿ Data manipulation operations like insert, update, delete, retrieve, filter, and sort.¿ Subqueries, joins and data formats for advanced data manipulation¿ Optimize database performance using indexes and views.¿ Examine closely advanced topics like transactions, procedures, functions, triggers, and administration.WHO THIS BOOK IS FORThis book is for anyone who wants to learn or improve their skills in using PostgreSQL. It is suitable for developers, data analysts, database administrators, and students who are interested in working with databases and building data-driven applications.

DESCRIPTIONTableau is one of the leading business intelligence and data visualization tools that fulfill almost all the requirements for getting insights from huge data and solving complex business queries using simple and complex visualizations. This book covers all the features supported by Tableau, from basics to advanced.Master data storytelling with Tableau by learning to connect, clean, and analyze data from various sources. This book covers essential chart types like bar, line, and pie charts while introducing advanced features like filters, LOD expressions, and dual-axis charts. Create interactive dashboards by combining visualizations, adding controls, and customizing designs to engage your audience. Use storytelling techniques to present insights effectively. With advanced visualizations like combo and Gantt charts, this guide equips you with the skills to communicate data clearly and make informed, data-driven decisions.This book begins with very basic information that even a beginner can understand. Gradually, the book covers intermediate and advanced features of Tableau, so it can help readers of all levels become experts in Tableau.WHAT YOU WILL LEARN¿ Understand different types of data sources and how to connect them.¿ Learn techniques for cleaning and preparing data for visualization.¿ Perform calculations, aggregations, and level of detail (LOD) expressions.¿ Create both, simple and advanced visualizations to present data.¿ Design visually engaging dashboards and storyboards to answer business questions effectively.WHO THIS BOOK IS FORThis book is for students and professionals who want to learn and have a rewarding career in data visualization using Tableau. It is also for anyone who wants to become a data analyst, Tableau developer, business analyst, etc.

DESCRIPTIONFor most modern-day data, graph data models are proving to be advantageous since they facilitate a diverse range of data analyses. This has spiked the interest and usage of graph databases, especially Neo4j. We study Neo4j and cypher along with various plugins that augment database capabilities in terms of data types or facilitate applications in data science and machine learning using plugins like graph data science (GDS).A significant portion of the book is focused on discussing the structure and usage of graph algorithms. Readers will gain insights into well-known algorithms like shortest path, PageRank, or Label Propagation among others, and how one can apply these algorithms in real-world scenarios within a Neo4j graph.Once readers become acquainted with the various algorithms applicable to graph analysis, we transition to data science problems. Here, we explore how a graph's structure and algorithms can enhance predictive modeling, prediction of connections in the graph, etc. In conclusion, we demonstrate that beyond its prowess in data analysis, Neo4j can be tweaked in a production setup to handle large data sets and queries at scale, allowing more complex and sophisticated analyses to come to life.KEY FEATURES¿ Utilizing graphs to improve search and recommendations on graph data models.¿ Understand GDS and Neo4j graph algorithms including cluster detection, link prediction, and centrality.¿ Complex problem-solving for predicting connections, application in ML pipelines and GNNs using graphs.WHAT YOU WILL LEARN¿ Understand Neo4j graphs and how to effectively query them with cypher.¿ Learn to employ graphs for effective search and recommendations around graph data.¿ Work with graph algorithms to solve problems like finding paths, centrality metrics, and detection of communities and clusters.¿ Explore Neo4j's GDS library through practical examples.¿ Integrate machine learning with Neo4j graphs, covering data prep, feature extraction, and model training.WHO THIS BOOK IS FORThe book is intended to serve as a reference for data scientists, business analysts, graph enthusiasts, and database developers and administrators who work or intend to work on extracting critical insights from graph-based data stores.

DESCRIPTIONIntroducing "Salesforce Automation with Salesforce Flow and Apex", a practical guide designed for anyone wanting to learn Salesforce automation. Whether you are just starting out or looking to build on your existing skills, this book is here to help you navigate the world of Salesforce flow and automation techniques.This book provides a comprehensive guide to Salesforce flow, a powerful automation tool within the Salesforce platform. It covers foundational concepts like flow types, elements, and debugging techniques. The book explains advanced topics such as screen flows, record-triggered flows, schedule-triggered flows, and platform event-triggered flows. It also explores the integration of flows with Apex to enhance functionality. Additionally, the book covers best practices for performance optimization, error handling, and security. It provides guidance on migrating from traditional automation tools like workflow rule and process builder to flow.By the end of this book, you will be ready to make a real impact with your Salesforce skills, driving efficiency and innovation in your organization.KEY FEATURES¿ A comprehensive introduction to Salesforce flow and automation with Apex and its benefits.¿ Practical guidance on creating and configuring user-friendly interfaces with screen flows.¿ Best practices for optimizing flow performance, handling errors, and ensuring security.WHAT YOU WILL LEARN¿ Grasp the importance of Salesforce automation and its transformative impact on business efficiency.¿ Explore Salesforce flow features and learn to create, debug, and optimize various flows, including screen and record-triggered flows.¿ Master autolaunched flows, integrate them with Apex, and enhance automation using platform events and scheduled flows.¿ Implement secure flow sharing, migrate from legacy automation tools, and integrate flows with external systems for seamless data exchange.¿ Combine flows and Apex triggers to build advanced, real-time automation solutions tailored to business needs.WHO THIS BOOK IS FORThis book is intended for Salesforce professionals, beginners, and students eager to learn automation within the Salesforce ecosystem. It is ideal for those pursuing roles such as Salesforce administrators, developers, business analysts, testers/QA, consultants, and architects.

DESCRIPTIONAdopting AI for Business Transformation offers a comprehensive guide for businesses ready to transition into AI and automation and transform their operations and ways of working. The book focuses on various industries providing practical insights and step-by-step guides for AI adoption and integration.Through real-world examples, expert insights, and case studies, the author shares his experience in product management, e-commerce, and digital platforms, presenting strategies for embracing AI and overcoming implementation challenges. Learn the key principles of AI adoption, get guidance on generative AI and large language models, and how to best leverage their power with advanced prompt engineering, organizational structures, workforce education and upskilling, cloud-based business models, and ready-to-use AI frameworks that have successfully transformed traditional businesses into AI-driven, modern, efficient business models.By the end of this book, you will understand how to adopt and integrate AI, empowering your team to leverage AI in your business operations, reducing the time spent on operational tasks, and unlocking new growth opportunities. By adopting the strategies in this book, you will reduce operational costs, improve efficiency, and future-proof your business.WHAT YOU WILL LEARN¿ Grasp how AI is revolutionizing business operations and driving innovation.¿ Understand AI adoption frameworks and learn how to choose the right one for your organization.¿ Explore AI applications in healthcare, finance, and manufacturing, from patient care to fraud detection.¿ Discover the role of AI in Web 3.0 and its intersection with blockchain.¿ Learn how AI enhances customer service, education, agriculture, and retail, transforming industry landscapes.WHO THIS BOOK IS FORThis book is ideal for CXOs, decision-makers, entrepreneurs, business owners and leaders, consultants, and digital transformation advisors interested in the democratization of AI, generative AI, and large language models.

DESCRIPTIONThis book explores how AI, blockchain, and the IoT can work together to build a more sustainable and efficient tech ecosystem. This book breaks down complex concepts, making them accessible to readers of all backgrounds. By focusing on the convergence of these technologies, it reveals how they are shaping a future where autonomous systems could operate independently of human intervention.This book explores the intersection of AI, blockchain, and robotics, covering their history, technology, and real-world applications. It explains decentralization and its technical foundations. The book also addresses ethical and practical issues, providing valuable insights for those interested in the future of technology and its impact on society. By examining AI, blockchain, and robotics both individually and in combination, it helps readers understand their potential and the broader implications for industries and communities.From privacy and security considerations to real-world case studies, this book offers a roadmap for understanding and leveraging the next wave of disruptive technologies. By the end, you will be equipped with a clear vision of the future and the knowledge to navigate it, empowered to make informed decisions about this exciting tech revolution.KEY FEATURES¿ Explores AI, blockchain, and robotics individually and in combination.¿ Provides historical context, technical explanations, practical applications, ethical considerations, and future outlook.¿ Features insights from experts and offers practical advice for individuals and organizations.WHAT YOU WILL LEARN¿ Convergence of AI, blockchain, and robotics to create autonomous ecosystems.¿ The potential impact of tech on industries and society.¿ Key privacy and security considerations in emerging technologies.¿ Real-world applications and case studies of tech integration.¿ The future of innovation and sustainable technological development.WHO THIS BOOK IS FORThis book explores emerging technologies at the concept level making it suitable for novice readers. Then, the convergence of these technologies are explored, eventually offering insights into building a sustainable, autonomous future.

DESCRIPTIONThis book offers a comprehensive overview of the Mendix platform from a developer's perspective. This powerful technology breaks down barriers, allowing anyone, with or without coding experience, to build custom applications quickly and efficiently with a solid foundation for platform evaluation.Key topics include Mendix's database design, page designer, and visual tools for creating functionality through microflows and nanoflows. You will also learn about security, best practices, and automated performance enhancements. Integration with other applications via REST, SOAP, and OData is explored, as well as the creation of web, progressive, and native mobile apps, all using the same low-code approach.By the end, you will be ready to begin your Mendix certification journey. You will have a thorough understanding of Mendix and through hands-on exercises. You will gain practical experience by developing a cloud-deployed Mendix application, positioning you for success in the fast-evolving low-code development landscape.KEY FEATURES¿ Step-by-step instructions for creating Mendix applications from scratch, with practical exercises to build hands-on experience.¿ Tips and tricks to optimize performance and maintainability of Mendix applications.¿ Real-world examples, case studies, and optimization tips to enhance Mendix application performance and maintainability.WHAT YOU WILL LEARN¿ Grasp the essentials of low-code development and discover how it speeds up application creation.¿ Build robust data models that mirror real-world structures for effective data representation.¿ Create intuitive and reusable user-friendly interfaces using Mendix's drag-and-drop tools, enhancing user experience.¿ To automate business processes with microflows, including complex decision-making and data manipulation.¿ To integrate Mendix applications with external systems using REST, SOAP, and OData APIs.¿ Advanced topics like security, integration, and mobile development.WHO THIS BOOK IS FORThis book is intended for new and seasoned developers that are starting their journey into low code development and business users evaluating low code software development. A programming background is helpful but not required to understand the content of the book.

DESCRIPTIONThis book teaches theory and coding examples to help readers design AI-powered cloud robotics applications. AI and robotics engineers will learn to build scalable systems, apply various methods for monitoring and prediction, and optimize systems to reduce costs and increase performance using the architectural techniques described.This book offers a detailed look into cloud robotics, starting with cloud computing basics and moving into its applications in robotics. It highlights the role of AI, ML, and computer vision in advancing robotic capabilities. This book also covers cloud robotics infrastructure, focusing on communication protocols and the ROS2 framework. Further, you will learn about building cloud-enabled robots and using AWS for AI and robotics. It addresses data privacy and security, concluding with real-world applications across various industries and insights into the future of cloud robotics.This book equips you with the foundational knowledge and practical skills to leverage the power of cloud computing to enhance the capabilities of robotic systems. You will gain the ability to design, develop, deploy, and manage cloud-enabled robots, pushing the boundaries of automation and innovation across various industries.WHAT YOU WILL LEARN¿ Understand cloud computing concepts, including service models, deployment models, and security.¿ Explore cloud robotics history, benefits, and AI integration in robotic systems.¿ Learn AI algorithms, ML, and deep learning for robotics applications.¿ Gain skills in computer vision, object detection, and enhancing robot perception using AI.¿ Master Robot Operating System 2 (ROS2) architecture and build cloud-enabled robots with hands-on experience.WHO THIS BOOK IS FORThe primary audience of this book is robotics engineers, AI engineers, and software developers with a basic understanding of robotics and cloud computing or no prior experience of the subject. This book contains practical code samples in Python and assumes that the reader has a fundamental understanding of Python programming.

DESCRIPTIONThe book "Problem Solving in Data Structures and Algorithms Using C++" is designed to equip readers with a solid foundation in data structures and algorithms, essential for both academic study and technical interviews.It provides a solid foundation in the field, covering essential topics such as algorithm analysis, problem-solving techniques, abstract data types, sorting, searching, linked lists, stacks, queues, trees, heaps, hash tables, graphs, string algorithms, algorithm design techniques, and complexity theory. The book presents a clear and concise explanation of each topic, supported by illustrative examples and exercises. It progresses logically, starting with fundamental concepts and gradually building upon them to explore more advanced topics. The book emphasizes problem-solving skills, offering numerous practice problems and solutions to help readers prepare for coding interviews and competitive programming challenges. Each problem is accompanied by a structured approach and step-by-step solution, enhancing the reader's ability to tackle complex algorithmic problems efficiently.By the end of the book, readers will have a strong understanding of algorithms and data structures, enabling them to design efficient and scalable solutions for a wide range of programming problems.KEY FEATURES¿ Learn essential data structures like arrays, linked lists, trees, and graphs through practical coding examples for real-world application.¿ Understand complex topics with step-by-step explanations and detailed diagrams, suitable for all experience levels.¿ Solve interview and competitive programming problems with C++ solutions for hands-on practice.WHAT YOU WILL LEARN¿ Master algorithmic techniques for sorting, searching, and recursion.¿ Solve complex problems using dynamic programming and greedy algorithms.¿ Optimize code performance with efficient algorithmic solutions.¿ Prepare effectively for coding interviews with real-world problem sets.¿ Develop strong debugging and analytical problem-solving skills.WHO THIS BOOK IS FORThis book is for computer science students, software developers, and anyone preparing for coding interviews. The book's clear explanations and practical examples make it accessible to both beginners and experienced programmers.