Bøger udgivet af BPB Publications

Blockchain revolution: Pioneering the next wave of digital innovation¿¿DESCRIPTION Blockchain secures individual transactions with cryptography, creating a tamper-proof chain. In contrast, distributed ledger technologies cover various technologies that may not adhere strictly to blockchain's specific structure.We will start the book by defining blockchain elements, comparing it to DLT, exploring security mechanisms, and looking at Bitcoin's history, transactions, wallets, keys, mining, and forensics. Further in the book, we will explore Ethereum's evolution, Ethereum virtual machine, and smart contracts. We will also discover permissioned blockchains with Hyperledger Fabric and understand crypto assets, ERC20, ERC721 tokens, NFTs, and cryptocurrencies. With real-world examples and practical insights, you will gain a solid grasp of the fundamentals and practical applications that make blockchain a game-changer in various industries. By the end of this book, you will be equipped with the understanding of blockchain technology, its potential applications, and its impact on the future. You will be able to confidently discuss blockchain concepts and evaluate its potential for your own projects.WHAT YOU WILL LEARN¿ Concept of distributed ledger system and blockchain.¿ Concept of consensus and mining in blockchain through the Bitcoin network.¿ Understanding Ethereum and develop-deploy smart contracts using different tools and frameworks.¿ Exploring permissioned blockchain and Hyperledger Fabric.¿ Applying blockchain to different domains such as IoT, AI, and cybersecurity.WHO THIS BOOK IS FORWhether you are a student, developer, entrepreneur, or curious individual, this book is your gateway to unlock the possibilities that blockchain and DLT bring to the forefront of innovation.

DESCRIPTION Recursion, a fundamental programming concept, empowers developers to solve complex problems elegantly and efficiently. However, excelling at recursion can be challenging due to its counterintuitive nature. This book is your comprehensive guide to understanding and applying recursion in your programming journey.This book is a complete guide to understanding recursion, starting from the basics and moving to more complex topics. It explains what recursion is and how it is different from iteration, using easy examples like calculating the factorial of a number, raising numbers to a power, and the Fibonacci sequence. The book then goes into more advanced topics like backtracking, dynamic programming, and tree traversal. It shows how to break big problems into smaller, manageable parts and how to make solutions faster with memoization. Real-world examples like the knapsack problem and finding the shortest path in a network are included.By the end of this book, readers will have a strong grasp of recursion, understanding not just how it works but also its practical applications. They will learn about Big O notation, which is crucial for evaluating the performance and efficiency of algorithms. Additionally, they will become familiar with function stacks, which play a vital role in understanding how recursive calls are managed in memory. KEY FEATURES ¿ Master recursion fundamentals and apply them to real-world problems.¿ Explore advanced recursion techniques and optimization strategies.¿ Gain hands-on experience with practical recursion examples.WHAT YOU WILL LEARN¿ Understand the basics of recursive algorithms and their nature.¿ Learn to plan, write, and stop recursion with boundary conditions.¿ Analyze recursive algorithm efficiency using Big O notation.¿ Differentiate between classical recursion and backtracking techniques.¿ Optimize recursion with memorization to improve performance.WHO THIS BOOK IS FORThe target audience for this book includes any programmer or engineer from diverse professional or academic backgrounds. This book can also be resourceful for anyone who wants to take programming industry job interviews, where often some basic recursive questions are asked to be solved quickly on site.

DESCRIPTION Chaos Engineering with Go is your essential guide to building resilient systems. In today's complex distributed environments, ensuring system reliability is paramount. By introducing controlled chaos into your systems, you can identify weaknesses and fortify them before they become critical failures. This book explores chaos engineering, offering a complete guide to building resilient systems. Starting with basic concepts and Go programming, it moves to chaos engineering topics like fault tolerance, fault injection, and chaos testing. Readers will learn to design and run chaos experiments using various tools and techniques. The book highlights the importance of monitoring and observability to understand system behavior. It includes practical case studies and best practices, ending with an in-depth look at security chaos engineering and emerging technologies. This book also emphasizes implementing observability practices within chaos engineering workflows, enhancing your ability to reduce downtime and improve system reliability.With a keen focus on best practices and lessons learned, this book equips readers with the knowledge and tools needed to embrace chaos, ensuring robust and reliable systems in an ever-evolving digital landscape. KEY FEATURES ¿ Master the core concepts and unique principles of chaos engineering.¿ Resilience patterns for unstoppable microservices.¿ Hands-on chaos experiments for real-world resilience.WHAT YOU WILL LEARN¿ Grasp fundamental concepts and principles of chaos engineering.¿ Implement fault tolerance and resilience patterns using Go.¿ Design and execute effective chaos experiments to test system resilience.¿ Utilize cutting-edge tools for chaos testing and fault injection.¿ Integrate observability practices into chaos engineering workflows.¿ Apply security chaos engineering and learn from real-world case studies.WHO THIS BOOK IS FORThe book caters to both beginners and experienced professionals interested in enhancing system integrity and reducing downtime. Ideal for site reliability engineers (SREs), DevOps engineers, enterprise architects, tech professionals, and college students.

DESCRIPTION Building Intelligent Applications with Generative AI is a comprehensive guide that unlocks the power of generative AI for building cutting-edge applications. This book covers a wide range of use cases and practical examples, from text generation and conversational agents to creative media generation and code completion. These examples are designed to help you capitalize on the potential of generative AI in your applications.Through clear explanations, step-by-step tutorials, and real-world case studies, you will learn how to prepare data and train generative AI models. You will also explore different generative AI techniques, including large language models like GPT-4, ChatGPT, Llama 2, and Google's Gemini, to understand how they can be applied in various domains, such as content generation, virtual assistants, and code generation. With a focus on practical implementation, this book also examines ethical considerations, best practices, and future trends in generative AI. Further, this book concludes by exploring ethical considerations and best practices for building responsible GAI applications, ensuring you are harnessing this technology for good. By the end of this book, you will be well-equipped to leverage the power of GAI to build intelligent applications and unleash your creativity in innovative ways.WHAT YOU WILL LEARN¿ Understand generative AI (GAI) and large language models (LLMs).¿ Explore real-world GAI applications across industries.¿ Build intelligent applications with the ChatGPT API.¿ Explore retrieval augmented generation with LangChain and Gemini Pro.¿ Create chatbots with LangChain and Streamlit for data retrieval.WHO THIS BOOK IS FORThis book is for developers, data scientists, AI practitioners, and tech enthusiasts who are interested in leveraging generative AI techniques to build intelligent applications across various domains.

DESCRIPTION "High-Performance Algorithmic Trading using AI" is a comprehensive guide designed to empower both beginners and experienced professionals in the finance industry. This book equips you with the knowledge and tools to build sophisticated, high-performance trading systems. It starts with basics like data preprocessing, feature engineering, and ML. Then, it moves to advanced topics, such as strategy development, backtesting, platform integration using Python for financial modeling, and the implementation of AI models on trading platforms. Each chapter is crafted to equip readers with actionable skills, ranging from extracting insights from vast datasets to developing and optimizing trading algorithms using Python's extensive libraries. It includes real-world case studies and advanced techniques like deep learning and reinforcement learning. The book wraps up with future trends, challenges, and opportunities in algorithmic trading.Become a proficient algorithmic trader capable of designing, developing, and deploying profitable trading systems. It not only provides theoretical knowledge but also emphasizes hands-on practice and real-world applications, ensuring you can confidently navigate and leverage AI in your trading strategies. WHAT YOU WILL LEARN¿ Develop AI-powered trading algorithms for enhanced decision-making and profitability.¿ Utilize Python tools and libraries for financial modeling and analysis.¿ Extract actionable insights from large datasets for informed trading decisions.¿ Implement and optimize AI models within popular trading platforms.¿ Apply risk management strategies to safeguard and optimize investments.¿ Understand emerging technologies like quantum computing and blockchain in finance.WHO THIS BOOK IS FORThis book is for financial professionals, analysts, traders, and tech enthusiasts with a basic understanding of finance and programming.

DESCRIPTION "Exam Prep AZ-305: Designing Microsoft Azure Infrastructure Solutions" book is a comprehensive guide for IT professionals preparing for the Microsoft Azure AZ-305 certification exam. This book offers detailed insights into designing scalable, secure, and resilient infrastructure solutions on the Azure platform, aligning with the latest exam objectives. It covers critical topics such as designing governance, security, storage, and networking solutions, ensuring readers have the necessary knowledge to architect effective Azure solutions. Through a blend of theoretical concepts and practical exercises, this guide equips readers with the skills needed to apply Azure best practices in real-world scenarios. Each chapter covers specific areas of infrastructure design, providing step-by-step instructions, expert tips, and real-life examples to illustrate complex concepts. This practical approach not only helps in mastering the exam content but also enhances the reader's ability to solve real-world challenges in their job roles.It not only prepares you for certification but also empowers you to design and implement robust Azure infrastructure solutions, thereby enhancing your capabilities and career prospects in the evolving field of cloud technology.WHAT YOU WILL LEARN¿ Master Azure governance principles.¿ Design secure authentication and authorization solutions.¿ Architect scalable compute solutions on Azure.¿ Implement effective data storage and integration strategies.¿ Design robust backup and disaster recovery solutions.¿ Learn key migration strategies for transitioning to Azure.WHO THIS BOOK IS FORWhether you are an aspiring cloud architect, a seasoned IT professional, or someone looking to advance their career in cloud computing, this book serves as an essential resource.

DESCRIPTION Swift, Apple's intuitive and feature-rich programming language, has revolutionized the landscape of app development. Its clear syntax and powerful capabilities make it a go-to choice for developers of all levels. Swift Design Patterns' brings an exciting set of design patterns that makes the process of app development simpler, quicker and error-free.Understand, implement, and run the various design patterns such as architectural patterns, creative patterns, behavioral patterns and structural patterns. The book teaches each of these patterns in detail, explores its coding, architecture, principle components and layers, and how they work together to build robust and efficient Swift applications. While doing so, it also explores the most effective design tools, Figma and Zeplin, and how to use them effectively.By the end of this book, you will be equipped with the knowledge and skills to design and implement complex Swift applications using proven design patterns. You will be able to write cleaner, more efficient, and reusable code, making you a more proficient Swift developer.KEY FEATURES ¿ Comprehensive coverage of essential Swift design patterns.¿ Learn to apply design patterns effectively in Swift projects through real-world examples and code snippets.¿ Learn proven techniques for writing clean, efficient, and maintainable Swift code.WHAT YOU WILL LEARN¿ Implement essential Swift design patterns in your projects.¿ Write clean, maintainable code and design scalable apps using SOLID and architectural patterns.¿ Reactive programming with RxSwift and testing with XCTest.¿ Collaborate effectively with design teams using Zeplin and Figma.WHO THIS BOOK IS FORApplication developer, Swift programmer, iOS Application Engineer and all software programmers who know Swift and want to develop efficient and high-performing applications with minimal time and high quality of codes.

"Mastering Data Visualization with Tableau" is an invaluable book that will help you become more knowledgeable and elevate your understanding and skills in data visualization using Tableau which is one of the leading tools in the industry. This comprehensive resource covers the basics of visual analytics, explaining both the theory and practical ways to turn raw data into useful insights.You will start with Tableau Desktop by learning to download it, navigate the interface, and connect to data sources. The book teaches you to create and format basic charts, adding interactivity with parameters, sets, sorting, and filtering. You will explore calculations and advanced visualizations like bar-in-bar charts and maps. It covers designing interactive dashboards, using text and images for storytelling, and sharing work via PDFs and Tableau Public. The book ends with AI features in Tableau and hands-on exercises to practice.Through this book, readers can gain the confidence to handle complex datasets, apply advanced visualization techniques, and harness Tableau's full potential to make informed decisions faster and with greater accuracy. KEY FEATURES ¿ Detailed exploration of Tableau, Tableau interface, dimensions, measures, and other visualization tools.¿ Techniques for interactive data visualization using actions, filters, sets, parameters, groups, and hierarchy.¿ Advanced graphing techniques and dynamic visualization strategies, calculated fields, table calculations, and LOD.WHAT YOU WILL LEARN¿ Tableau for complex data visualizations and apply predictive analytics. Clean and prepare data efficiently and create interactive dashboards that drive strategic business decisions.¿ Advanced charts like bar-in-bar, profit calendar, and map visualizations.¿ Gain practical hands-on experience with a question bank based on various industry use cases, enhancing your ability to tackle real-world data challenges.WHO THIS BOOK IS FORThis book is an excellent resource for students from any discipline, data scientists, business analysts, and professionals eager to master Tableau for comprehensive insights, effective dashboards, and advanced data analysis.

DESCRIPTION In today's rapidly evolving technological landscape, staying competitive in the field of software development requires a deep understanding of fundamental programming concepts and the ability to solve complex problems efficiently. This book aims to be your comprehensive guide to acing technical interviews in C, C++, data structures, and database management systems (DBMS).The journey to becoming a proficient software engineer is often paved with rigorous technical interviews that test your knowledge, problem-solving abilities, and coding skills. This book compiles a wide range of interview questions and answers, providing you with the insights and practice needed to excel in any technical interview.Each chapter includes a series of questions that range from basic to advanced levels. The questions are designed to test various aspects of your knowledge and problem-solving skills. Detailed solutions and explanations are provided to help you understand the reasoning behind each answer.KEY FEATURES ¿ Understand arrays, linked lists, stacks, queues, trees, and graphs for problem-solving.¿ Learn time and space complexity for solution optimization.¿ Learn advanced concepts of C, C++, data structures, and DBMS.WHAT YOU WILL LEARN¿ Advanced topics about C, C++, DBMS, and data structures.¿ Understand pointers, including pointer arithmetic and multi-level pointers.¿ Utilize templates and the Standard Template Library for generic and efficient code.¿ Algorithmic thinking and problem-solving techniques specific to data structures and algorithms.WHO THIS BOOK IS FORThis book is ideal for students and graduates preparing for campus placements or entry-level positions, professionals seeking job transitions, and self-learners aiming to enhance their programming and problem-solving skills.

DESCRIPTION The Modern Software Engineering Guidebook makes an effort to explain how one may pursue a noteworthy career in emerging technologies. Through a series of steps, this book helps the reader gain a deeper awareness of the factors that influence one's career and progressive values. This book's focus is on conceptual entities, with an emphasis on moving forward with more modern software engineering advancement methodologies.The book guides how readers should investigate and take advantage of untapped prospects while focusing on critical areas of their careers. Starting with the software development lifecycle (SDLC) and its steps like gathering requirements, design, coding, testing, and maintenance. Learn methods like waterfall and agile, and how to write a software requirements document (SRD). It includes design principles, object-oriented design (OOD), and coding best practices. The book also discusses software reliability, testing methods, and measuring code quality. Find tips on managing software changes and maintenance. Lastly, explore trends like DevOps, cloud development, and using AI and ML in software.With the help of this book, readers will find it simpler to increase their employability and relevance to the job market, enabling them to quickly advance into fulfilling careers.KEY FEATURES ● Learn the phases of software engineering, including requirements, design, coding, testing, and maintenance.● Understand software design, structured coding techniques, and testing strategies to ensure quality and reliability.● Get familiar with project planning, current trends like software reliability, reuse, and the importance of quality assurance and reviews.WHAT YOU WILL LEARN● Understand the phases of software engineering and the latest advancements in software engineering.● Grasp the importance of data gathering, analysis, and design.● Master design architecture and structured coding styles.● Understand different testing concepts and methods.● Get familiar with maintenance tools and software quality metrics.WHO THIS BOOK IS FORThis book targets aspiring and intermediate software developers seeking a solid foundation in SDLC. It benefits programmers, engineers, and IT professionals who want to create high-quality software.

DESCRIPTIONStatistics is an important skill set to have when working as a quality analyst, a mathematician, a data analyst, a software engineer, or any analytical job. This book, "Implementing Statistics with Python," will teach you the basics of statistics and how to use Python to analyze data. You will learn to find patterns, quantify uncertainty, and make data-driven predictions with confidence. You will start with basic statistics and then use Python libraries like NumPy and Pandas for data manipulation. You will also learn data visualization with Matplotlib and Seaborn to create informative charts. The book covers probability theory and statistical inference to help you make data-driven decisions. You will be exploring regression and time series analysis with ARIMA for forecasting. Finally, the book introduces ML algorithms, preparing you for real-world data science projects.The book focuses on applying statistics rather than theory, using popular libraries like NumPy, SciPy, Pandas, Matplotlib, and Scikit-Learn. Reading this book will give you a good foundation for working with ML, business analytics, and data-driven business challenges.KEY FEATURES ● Learn the various aspects of statistics and its applications in real-world scenarios.● Learn about the various libraries in Python for working with data.● Adopt the learn-by-doing approach to solve real-world statistics problems.● Learn how statistics is applied to Machine Learning.WHAT YOU WILL LEARN● Learn the fundamentals of Python and its libraries like Numpy, Pandas, Matplotlib and Seaborn.● Grasp descriptive statistics and probability concepts.● Perform statistical inference with Chi-square, ANOVA, and regression analysis.● Skillfully navigate multivariate and time series analysis.● Apply statistical techniques in practical ML.WHO THIS BOOK IS FORThis book is for readers with basic Python knowledge who want to apply statistics in real-life scenarios, and those pursuing careers in data analytics, data engineering, data science, ML, and AI. It is also ideal for students beginning a course in statistics.

DESCRIPTION In today's era of Artificial Intelligence and the vast expanse of big data, understanding how to effectively utilize search algorithms has become crucial. Every day, billions of searches happen online, influencing everything from social media recommendations to critical decisions in fields like finance and healthcare. Behind these seemingly straightforward searches are powerful algorithms that determine how information is discovered, organized, and applied, fundamentally shaping our digital interactions. This book covers various search algorithms, starting with linear and binary searches, analyzing their performance, and implementing them in Python. It progresses to graph traversal algorithms like DFS and BFS, including Python examples and explores the A* algorithm for optimal pathfinding. Advanced search techniques and optimization best practices are discussed, along with neural network applications like gradient descent. You will also learn to create interactive visualizations using Streamlit and explore real-world applications in gaming, logistics, and Machine Learning.KEY FEATURES ¿ Comprehensive coverage of a wide range of search algorithms, from basic to advanced. ¿ Hands-on Python code examples for each algorithm, fostering practical learning.¿ Insights into the real-world applications of each algorithm, preparing readers for real-world challenges.WHAT YOU WILL LEARN¿ Understand basic to advanced search algorithms in Python that are crucial for information retrieval.¿ Learn different search methods like binary search and A* search, and their pros and cons.¿ Use Python's visualization tools to see algorithms in action for better understanding.¿ Enhance learning with practical examples, challenges, and solutions to boost programming skills.WHO THIS BOOK IS FORThis book is for software engineers, data scientists, and computer science students looking to master search algorithms with Python to optimize search algorithms in today's data-driven environments.

This book establishes a strong foundation by explaining core concepts like operating systems, networking, and databases. Understanding these systems forms the bedrock for comprehending security threats and vulnerabilities. The book gives aspiring information security professionals the knowledge and skills to confidently land their dream job in this dynamic field.This beginner-friendly cybersecurity guide helps you safely navigate the digital world. The reader will also learn about operating systems like Windows, Linux, and UNIX, as well as secure server management. We will also understand networking with TCP/IP and packet analysis, master SQL queries, and fortify databases against threats like SQL injection. Discover proactive security with threat modeling, penetration testing, and secure coding. Protect web apps from OWASP/SANS vulnerabilities and secure networks with pentesting and firewalls. Finally, explore cloud security best practices using AWS to identify misconfigurations and strengthen your cloud setup.The book will prepare you for cybersecurity job interviews, helping you start a successful career in information security. The book provides essential techniques and knowledge to confidently tackle interview challenges and secure a rewarding role in the cybersecurity field.KEY FEATURES ¿ Grasp the core security concepts like operating systems, networking, and databases.¿ Learn hands-on techniques in penetration testing and scripting languages.¿ Read about security in-practice and gain industry-coveted knowledge.WHAT YOU WILL LEARN¿ Understand the fundamentals of operating systems, networking, and databases.¿ Apply secure coding practices and implement effective security measures.¿ Navigate the complexities of cloud security and secure CI/CD pipelines. ¿ Utilize Python, Bash, and PowerShell to automate security tasks.¿ Grasp the importance of security awareness and adhere to compliance regulations.WHO THIS BOOK IS FORIf you are a fresher or an aspiring professional eager to kickstart your career in cybersecurity, this book is tailor-made for you.

This book intends to provide a collection of various MCQs on data scienceDESCRIPTION This book is a comprehensive manual created to assess and improve your comprehension of many concepts and methodologies in data science. The course encompasses a broad spectrum of subjects, such as data preprocessing, Machine Learning techniques, data visualization, statistical analysis, and additional topics. Every chapter is organized with a series of multiple-choice questions that test your understanding and allow you to evaluate your expertise in the subject. The book's objective is to offer a pragmatic and captivating approach for readers to enhance their proficiency in data science through practical exercises. The book provides an extensive examination of several subjects in data science, encompassing data preprocessing, statistical analysis, Machine Learning techniques, data visualization, and additional areas. This extensive knowledge helps readers acquire a full and all-encompassing comprehension of the subject matter. The chapters in this book adhere to a structured framework, which includes multiple-choice questions that enable readers to assess their understanding and grasp of the content. KEY FEATURES ¿ Comprehensive coverage of data science concepts and features.¿ Multiple-choice questions to test and assess knowledge effectively.¿ Over 5000 multiple-choice questions for practice.WHAT YOU WILL LEARN¿ Mastering data science concepts through multiple-choice questions.¿ Strengthening problem-solving skills by practicing diverse scenarios.¿ Interpreting the results of data analyses and Machine Learning models effectively.¿ Evaluating the performance of different Machine Learning models using metrics.¿ Developing critical thinking skills to assess the suitability of various data science approaches.¿ Preparing for exams, interviews, and quizzes, etc.WHO THIS BOOK IS FORThis data science MCQ book is perfect for anyone looking to test and improve their knowledge of data through multiple-choice questions.

DESCRIPTION Our book is divided into several useful concepts and techniques of machine learning. This book serves as a valuable resource for individuals seeking to deepen their understanding of advanced topics in this field. Learn about various learning algorithms, including supervised, unsupervised, and reinforcement learning, and their mathematical foundations. Discover the significance of feature engineering and selection for enhancing model performance. Understand model evaluation metrics like accuracy, precision, recall, and F1-score, along with techniques like cross-validation and grid search for model selection. Explore ensemble learning methods along with deep learning, unsupervised learning, time series analysis, and reinforcement learning techniques. Lastly, uncover real-world applications of the machine and deep learning algorithms.After reading this book, readers will gain a comprehensive understanding of machine learning fundamentals and advanced techniques. With this knowledge, readers will be equipped to tackle real-world problems, make informed decisions, and develop innovative solutions using machine and deep learning algorithms.WHAT YOU WILL LEARN¿ Ability to tackle complex machine learning problems.¿ Understanding of foundations, algorithms, ethical issues and how to implement each learning algorithm for their own use/ with their data.¿ Efficient data analysis for real-time data will be understood by researchers/ students.¿ Using data analysis in near future topics and cutting-edge technologies.WHO THIS BOOK IS FORThis book is ideal for students, professors, and researchers. It equips industry experts and academics with the technical know-how and practical implementations of machine learning algorithms.

Strengthening networks, redefining security: ELK Stack leading the chargeDESCRIPTION Step into the dynamic world of zero trust network architecture with this comprehensive handbook. Starting with an exploration of zero trust principles, each chapter unveils new insights and practical strategies. From crafting strategic blueprints to implementing hands-on deployment tactics, discover the intricacies of building a resilient zero trust network capable of thwarting modern threats.Journey through the extensive capabilities of ELK Stack, essential for fortifying a zero trust paradigm. Learn the nuances of data acquisition strategies and efficient ingestion methods with ELK, enabling robust data visualization and dashboard creation using Kibana. Explore advanced functionalities like Machine Learning driven anomaly detection to enhance your defenses against emerging threats. Explore Elastic Security's suite, encompassing threat detection, incident response, and compliance reporting, crucial elements in strengthening network defenses. Utilize the transformative potential of Zeek in network security, from foundational principles to advanced integration with Elastic Security. Real-world case studies showcase the synergy between Zeek and Elastic Security, providing insights into future-proof network protection strategies.Arm yourself with the knowledge and tools necessary to navigate the evolving landscape of network security. Traverse the realms of zero trust architecture, ELK Stack, and Elastic Security, empowered by practical insights and real-world applications.WHAT YOU WILL LEARN¿ Understanding the core principles and intricacies of zero trust network architecture.¿ Designing and deploying a robust zero trust network using strategic methodologies.¿ Leveraging ELK Stack's capabilities to support and enhance a zero trust approach.¿ Implementing effective data gathering and ingestion strategies with ELK.¿ Mastering data visualization and dashboard creation using Kibana for actionable insights.WHO THIS BOOK IS FORThe book is primarily aimed at security professionals, network architects, and IT managers who are responsible for securing their organization's network infrastructure and sensitive data. The book is suitable for both technical and non-technical readers.

Quickly master Kotlin by practicing what you learnDESCRIPTION Kotlin Crash Course is a fast-paced, hands-on introduction to Kotlin, preparing readers to build robust applications efficiently using the latest language features and best practices.The book is divided into comprehensive chapters that cover key Kotlin programming topics such as object-oriented and functional programming, collections, concurrency, and unit testing. Each chapter takes a learning by doing approach, focusing on practical projects rather than solely theoretical knowledge. This strategy improves knowledge retention by simulating real-life experiences, allowing students to apply concepts in practice as they learn them. Furthermore, the book is interwoven with an abundance of best practices obtained from industry experience. This approach ensures that even beginners can gain seasoned insights and apply their knowledge confidently to real-world challenges.By the end of this comprehensive course, you will not only possess a strong foundation in Kotlin programming but also the practical skills to build real-world applications, including REST APIs and serverless applications leveraging Kotlin's cloud capabilities.WHAT YOU WILL LEARN¿ Understand Kotlin syntax and basic coding conventions.¿ Master object-oriented and functional programming concepts.¿ Utilize Kotlin's collection framework effectively.¿ Implement concurrency and parallelism with coroutines.¿ Build robust applications with best practices.¿ Develop diverse applications, including REST APIs and serverless solutions.WHO THIS BOOK IS FORThis book is suitable for students, programmers from other languages, Java developers, back-end developers, full-stack developers, and mobile developers. The book is appropriate for both new and experienced programmers wishing to acquire or refresh their Kotlin skills.

More figures will bridge the gap between mathematics and visualization of the communication systemKEY FEATURES ¿ More figures to visualize the communication system.¿ Limited mathematics to explain the concept.¿ Complete overview of the communication system.DESCRIPTION In today's tech-driven world, communication systems play a crucial role in sharing information effectively. The book, Analog and Digital Communication helps you grasp the fundamental principles of these systems, enabling you to analyze and visualize information flow.This book on communication systems teaches you the basics of how information travels. It covers key concepts and tools, showing how analog information is transmitted on a carrier signal using techniques like AM and FM. You will also learn about converting analog signals to digital data and using modulation techniques like ASK and PSK. The book explains handling noise in communication and introduces information theory to understand data capacity and noise impact. It covers performance metrics like BER and channel coding for error correction. Additionally, it explores wireless and optical communication technologies like cellular networks, Wi-Fi, and optical fiber communication.By the end of this book, you will master analyzing digital modulation, understanding noise in communication, and using error correction methods. You will explore modern wireless and optical communication with light pulses, gaining skills to navigate the communication world confidently.WHAT YOU WILL LEARN¿ Visualize communication techniques.¿ Relate the mathematical expressions with communication techniques.¿ Find out the importance of different parameters in the performance of the communication system.¿ Understand the impact of noise and techniques to overcome it.WHO THIS BOOK IS FORThis book is suitable for undergraduate ECE students in all universities, as well as students of ICT and anyone interested in communication. It is ideal for engineering students, aspiring communication professionals, and curious individuals seeking insights into the technology connecting our world.

The book is designed for a practical approach to learning, with examples based on scenarios. It covers possible OSINT blueprints from the beginning to an advanced levelDESCRIPTION OSINT is a powerful technology used to gather and analyze information from publicly available sources. It empowers cybersecurity professionals to proactively detect and mitigate threats. This book serves as a comprehensive guide offering strategic approaches and practical insights into leveraging OSINT for cybersecurity defense.This book is an all-encompassing guide to open-source intelligence (OSINT). It meticulously details tools, techniques, and applications across a multitude of domains. The book explores OSINT's use in social media, email domains, IP addresses, images, videos, documents, mobile numbers, companies, job postings, and the dark web. It probes OSINT's application for threat intelligence, data leak detection, understanding encryption, and digital certificates, assessing fake news, reverse image search, geolocation workarounds, real image identification, finding banned organizations, handling sensitive information like Aadhar and Social Security Numbers, while also tracking fraudulent SMS.By the end of this book, readers will emerge as competent cybersecurity professionals equipped with the skills and expertise to navigate the ever-evolving landscape of cyber threats with confidence and proficiency.KEY FEATURES ¿ Learn about OSINT and how to set up an OSINT environment for investigations.¿ Master techniques for tracking fraud SMS and investigating emails.WHAT YOU WILL LEARN¿ Understand the fundamentals of OSINT in cybersecurity.¿ Securing web browsers and ensuring online privacy.¿ Investigating emails and tracking cyber threats.¿ Gain insights into tracking mobile identities and domain or IP investigations.WHO THIS BOOK IS FORThis book is essential for cybersecurity professionals, investigators, law enforcement, and digital forensics analysts seeking advanced OSINT strategies.

Explore the world of Artificial Intelligence with a deep understanding of Machine Learning concepts and algorithmsKEY FEATURES ¿ A detailed study of mathematical concepts, Machine Learning concepts, and techniques.¿ Discusses methods for evaluating model performances and interpreting results.¿ Explores all types of Machine Learning (supervised, unsupervised, reinforcement, association rule mining, artificial neural network) in detail.DESCRIPTION "Simplified Machine Learning" is a comprehensive guide that navigates readers through the intricate landscape of Machine Learning, offering a balanced blend of theory, algorithms, and practical applications. The first section introduces foundational concepts such as supervised and unsupervised learning, regression, classification, clustering, and feature engineering, providing a solid base in Machine Learning theory. The second section explores algorithms like decision trees, support vector machines, and neural networks, explaining their functions, strengths, and limitations, with a special focus on deep learning, reinforcement learning, and ensemble methods. The book also covers essential topics like model evaluation, hyperparameter tuning, and model interpretability. The final section transitions from theory to practice, equipping readers with hands-on experience in deploying models, building scalable systems, and understanding ethical considerations.WHAT YOU WILL LEARN¿ Solid foundation in Machine Learning principles, algorithms, and methodologies.¿ Implementation of Machine Learning models using popular libraries like NumPy, Pandas, PyTorch, or scikit-learn.¿ Knowledge about selecting appropriate models, evaluating their performance, and tuning hyperparameters.¿ Techniques to pre-process and engineer features for Machine Learning models.¿ To frame real-world problems as Machine Learning tasks and apply appropriate techniques to solve them.WHO THIS BOOK IS FORThis book is designed for a diverse audience interested in Machine Learning, a core branch of Artificial Intelligence. Its intellectual coverage will benefit students, programmers, researchers, educators, AI enthusiasts, software engineers, and data scientists.

Crafting elegant and efficient solutions!KEY FEATURES ¿ Learn core functional programming (FP) concepts and their advantages for Go development.¿ Implement practical techniques like closures, higher-order functions, and function currying for powerful codes.¿ Write clean and maintainable code using immutability and pure functions.DESCRIPTION "Functional Programming with Go" is a comprehensive guide to introduce Go developers to the powerful concepts of functional programming. This book covers topics like first-class functions, closures, higher-order functions, immutability, and pure functions. It also demonstrates how these principles can enhance code quality, reliability, and maintainability.Starting with functional programming basics and setup, it covers first-class functions, closures, and higher-order functions like map, filter, and reduce. You will learn advanced techniques like currying, immutability, and functional error handling with monads. The book also explores concurrent programming with FP in Go, design patterns, functional web development, testing, debugging, and advanced topics like memoization.This book equips you with the knowledge and skills needed to write efficient, scalable, and robust Go applications. By the end of this book, you will have the knowledge and skills to apply functional programming principles in Go.WHAT YOU WILL LEARN¿ Applying functional programming concepts to enhance code quality.¿ Leveraging higher-order functions and closures for flexible code.¿ Implementing advanced techniques like function currying and partial application.¿ Writing pure functions and using immutable data structures in Go.¿ Handling errors efficiently using monads and functional techniques.¿ Designing concurrent systems with goroutines and channels in Go.WHO THIS BOOK IS FORThis book is designed for Go developers who want to enhance their skills in functional programming. It is also suitable for programmers with a basic understanding of Go.

Leverage the power of AI in coding, graphics, design, and intelligence to join the next wave in game developmentKEY FEATURES ¿ Teaches the core concepts of game development for 2D, 3D, and AI games.¿ Uses AI to assist and guide the reader across several facets of game development.¿ Learn to create AI-controlled enemies for your games.DESCRIPTION This book is a comprehensive guide to creating interactive and engaging games, leveraging the capabilities of ChatGPT and other advanced AI technologies. The book starts with prompt engineering and system prompting, building a strong AI foundation for game development. It covers various game genres, from text adventures to 3D shooters, showing AI integration. Each chapter is designed to build on the previous one, ensuring a cohesive learning experience that gradually increases in complexity and depth. Readers will learn game development basics and creative techniques for immersive game worlds. They will use PyZork for text games and Streamlit for enhanced visuals. The book covers AI-generated assets, behavior-driven AI, and advanced topics like isometric world-building and voice-responsive games. Practical projects help readers create their unique games, while GPT agents and AI technologies showcase the future of gaming.By the end of this journey, readers will have a deep understanding of how to create innovative and engaging games using AI, positioning them at the forefront of modern game development.WHAT YOU WILL LEARN¿ Master prompt engineering for building games, game assets, and AI-driven games.¿ Develop engaging text-based adventures with AI-driven storytelling elements.¿ Create 2D games from platformers, isometric worlds, and physics.¿ Design AI opponents with behavior-driven logic and adaptive difficulty.¿ Introduction to 3D first-person shooters using GPT agents.¿ Implement voice recognition and text-to-speech in interactive games.WHO THIS BOOK IS FORThis book is for aspiring or experienced game developers and indie game studios interested in using generative AI to create games faster and explore new possibilities.

Architecting AI: Design patterns for building deep learning productsKEY FEATURES ¿ Master foundational concepts in design patterns of deep learning.¿ Benefit from practical insights shared by an industry professional.¿ Learn to build data products using deep learning.DESCRIPTION Design Patterns of Deep Learning with TensorFlow is your comprehensive guide to learning deep learning from a design pattern perspective. In this book, we explore deep learning within the context of building hyper-personalization models, exploring its applications across various industries and scenarios. It starts by showing how deep learning enhances retail through customer segmentation and data analysis. You will learn neural networks, computer vision with CNNs, and NLP for analyzing customer behavior. This book addresses challenges like uneven data and optimizing models with techniques like backpropagation, hyperparameter tuning, and transfer learning. Finally, it covers setting up data pipelines and deploying your system. With practical tips and actionable advice, this book equips readers with the skills and strategies needed to thrive in today's competitive AI landscape.By the end of this book, you will be equipped with the knowledge and practical skills to build and deploy deep learning-powered hyper-personalization systems that deliver exceptional customer experiences.WHAT YOU WILL LEARN¿ Understand about hyper-personalized AI models for tailored user experiences.¿ Design principles of computer vision and NLP models.¿ Inner working of transformers equipping readers to understand the intricacies of generative AI and large language models (LLMs) like ChatGPT.¿ To get the best out of deep learning models through hyperparameter tuning and transfer learning.¿ Learn how to build deployment pipelines to serve models into production environments seamlessly.WHO THIS BOOK IS FORThis book caters to both beginners and experienced practitioners in the field of data science and Machine Learning. Through practical examples, it simplifies complex ideas, linking them to design patterns.

How to plan, design, manage, build, and run monoliths and microservices in an agnostic, scalable, and highly available cloud-native architecture with Kubernetes DESCRIPTION The book "Cloud Native Architecture" explains how to plan, manage, build, and run monoliths and microservices in an agnostic, scalable, and highly available cloud-native runtime such as Kubernetes. This is done by effectively applying DevOps principles through the tactical use of CNCF tools. You will start by learning about cloud-native technology's history and business reasons. This will help you understand its five key pillars: open-source, containers, distributed architectures, operational benefits, and DevOps integration. We will introduce a framework for adopting cloud-native best practices, focusing on technical and cultural changes. You will learn how to adapt processes like DevOps, Chaos Engineering, Automation, and API First. We will cover automating infrastructure with tools like Prometheus and Grafana, using Kubernetes for container management, and designing applications with microservices. Practical exercises will include setting up CI/CD pipelines with Jenkins and ensuring Kubernetes security. By the end of this book, you will be empowered to navigate the Cloud-Native landscape confidently, equipped with the knowledge and practical skills to design, develop, deploy, and migrate applications for the modern cloud era.WHAT YOU WILL LEARN¿ Learn about cloud native's background and its impact on culture and processes.¿ Understand Kubernetes concepts, components, and best practices with an agnostic framework.¿ Design and build monoliths incrementally on Kubernetes following twelve-factor app principles.¿ Transition from monoliths to microservices using specific tools for lifecycle management.¿ Address Kubernetes security during application development and deployment.WHO THIS BOOK IS FORThis book is for developers, architects, and solution consultants who are now exploring cloud-native architecture principles for design and development with Agile and DevOps to modernize existing applications or create brand-new cloud-native products.