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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.

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 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.

DESCRIPTIONPython is a simple, easy-to-learn, and one of the top programming languages across the globe. As a result of advancements in AI, data mining, and numerical computing fields, Python has become a popular programming language catering to various stakeholders. It is a powerful tool for working with a variety of data. This book provides the basics of Python and an introduction to data analytics.This book offers a complete introduction to Python programming, covering everything from the basics to the advanced topics. It starts by explaining core concepts like syntax and the Python interpreter, then dives into data structures, control flow, functions, and modules. You will also learn about data analysis and visualization with popular libraries like NumPy, Pandas, Matplotlib, and Seaborn. It wraps up with practical case studies, showing how to apply Python in real-world scenarios effectively.The book serves as a step-by-step guide to performing data analysis. Its content is designed so that even a novice can learn and perform data analysis and visualization simply by following the instructions in the book.KEY FEATURES¿ The book covers a wide range of topics, from Python fundamentals to advanced data analysis techniques.¿ It includes practical exercises and real-world case studies to illustrate the applications of Python for data analysis.WHAT YOU WILL LEARN¿ Understand the basics of programming languages and the role of the Python interpreter.¿ Read about different data structures like lists, sets, tuples, and dictionaries, and understand their applications.¿ Learn how to work with files in Python, including reading, writing, and appending data.¿ Discover how to use NumPy and Pandas for efficient data manipulation and analysis.¿ Learn how to create informative visualizations using Matplotlib and Seaborn.WHO THIS BOOK IS FORThis book is designed for students studying UG or PG courses in the computer science and applications domain. Learning Python is a simple way to begin the journey of data analytics. One of the in-demand domains in the job market, and research is data analytics. This book will be helpful for students interested in this domain.

DESCRIPTIONThis book provides a detailed introduction to digital forensics, covering core concepts, principles, and the role of various teams in incident response. From data acquisition to advanced forensics techniques, it equips readers with the skills to identify, analyze, and respond to security incidents effectively.It guides readers in setting up a private lab using Kali Linux, explores operating systems and storage devices, and dives into hands-on labs with tools like FTK Imager, volatility, and autopsy. By exploring industry-standard frameworks like NIST, SANS, and MITRE ATT&CK, the book offers a structured approach to incident response. Real-world case studies and practical applications ensure readers can apply their knowledge immediately, whether dealing with system breaches, memory forensics, or mobile device investigations, helping solve cybercrimes and protect organizations.This book is a must-have resource for mastering investigations using the power of Kali Linux and is ideal for security analysts, incident responders, and digital forensic investigators.WHAT YOU WILL LEARN¿ Conduct thorough digital forensics using Kali Linux's specialized tools.¿ Implement incident response frameworks like NIST, SANS, and MITRE ATT&CK.¿ Perform memory, registry, and mobile device forensics with practical tools.¿ Acquire and preserve data from cloud, mobile, and virtual systems.¿ Design and implement effective incident response playbooks.¿ Analyze system and browser artifacts to track malicious activities.WHO THIS BOOK IS FORThis book is aimed at cybersecurity professionals, security analysts, and incident responders who have a foundational understanding of digital forensics and incident response principles.

DESCRIPTION Data engineering is the art of building and managing data pipelines that enable efficient data flow for AI/ML projects. This book serves as a comprehensive guide to data engineering for AI/ML systems, equipping you with the knowledge and skills to create robust and scalable data infrastructure.This book covers everything from foundational concepts to advanced techniques. It begins by introducing the role of data engineering in AI/ML, followed by exploring the lifecycle of data, from data generation and collection to storage and management. Readers will learn how to design robust data pipelines, transform data, and deploy AI/ML models effectively for real-world applications. The book also explains security, privacy, and compliance, ensuring responsible data management. Finally, it explores future trends, including automation, real-time data processing, and advanced architectures, providing a forward-looking perspective on the evolution of data engineering.By the end of this book, you will have a deep understanding of the principles and practices of data engineering for AI/ML. You will be able to design and implement efficient data pipelines, select appropriate technologies, ensure data quality and security, and leverage data for building successful AI/ML models. KEY FEATURES ● Comprehensive guide to building scalable AI/ML data engineering pipelines.● Practical insights into data collection, storage, processing, and analysis.● Emphasis on data security, privacy, and emerging trends in AI/ML.WHAT YOU WILL LEARN● Architect scalable data solutions for AI/ML-driven applications.● Design and implement efficient data pipelines for machine learning.● Ensure data security and privacy in AI/ML systems.● Leverage emerging technologies in data engineering for AI/ML.● Optimize data transformation processes for enhanced model performance. WHO THIS BOOK IS FORThis book is ideal for software engineers, ML practitioners, IT professionals, and students wanting to master data pipelines for AI/ML. It is also valuable for developers and system architects aiming to expand their knowledge of data-driven technologies.

DESCRIPTION"Azure Cookbook" is a practical guide designed to help developers, system administrators, and cloud architects master Microsoft Azure through hands-on solutions. This book offers step-by-step recipes for tackling real-world challenges using Azure's vast range of services.This book covers many important topics related to Azure, such as storage, networking, virtual machines, containers, and application development. It offers practical tips and step-by-step instructions for creating and managing secure Azure applications. You will learn about various Azure services, including Azure Storage, Virtual Networks, App Service, and Azure Security Center. Whether you are new to Azure or have some experience, this guide will help you gain the skills needed to use Azure effectively for your cloud computing projects.With this book, you will not only enhance your Azure skills but also apply them directly to your job roles. By mastering the cloud, you will be equipped to design, deploy, and manage robust, scalable solutions-making you an invaluable asset in today's cloud-driven world.KEY FEATURES¿ Step-by-step Azure recipes for real-world cloud solutions mastery.¿ Troubleshoot Azure issues with expert tips and hands-on guidance.¿ Boost skills with practical examples from core to advanced services.WHAT YOU WILL LEARN¿ Deploying and managing Azure Virtual Machines, Networks, and Storage solutions.¿ Automating cloud infrastructure using Bicep, ARM templates, and PowerShell.¿ Implementing secure, scalable, and cost-effective cloud architectures.¿ Building containerized apps with Azure Kubernetes Service (AKS).¿ Creating serverless solutions using Azure Functions and Logic Apps.¿ Troubleshooting Azure issues and optimizing performance for production workloads.WHO THIS BOOK IS FORThis book is for developers, cloud engineers, system administrators, and architects looking to deepen their understanding of Microsoft Azure and want to learn how to effectively utilize Azure for their cloud computing needs.

DESCRIPTION Azure FinOps, the intersection of finance, operations, and technology, has become paramount in optimizing cloud spending. "Azure FinOps Essentials "is a guide to help you navigate easily with cost management and optimization within Microsoft Cloud. This book is a practical guide to cutting cloud costs in Microsoft Azure. It covers everything from understanding Azure services and cost management to advanced strategies like Infrastructure as Code and serverless computing. You will learn to set up Azure Cost Management, optimize resources with tools like Reserved Instances, and enforce governance using Azure Policy. The book also highlights case studies and best practices to help you build a FinOps culture, streamline costs, and enhance cost-efficiency in your cloud environment.If you are new to cloud financial management or need a refresher on some of the best practices, Azure FinOps Essentials is designed for anyone running an operational workload in both public and private clouds who wants to improve their expense management within the environment.KEY FEATURES ¿ An in-depth guide to the fundamentals of Azure cost management.¿ Detailed instructions for creating cost alerts and establishing budgets.¿ Practical strategies to enhance cloud resource efficiency.WHAT YOU WILL LEARN¿ Establish and enforce standards for Azure cloud cost management through auditing.¿ Learn cost-saving tactics like rightsizing and using Reserved Instances.¿ Master Azure tools for monitoring spending, budgeting, and setting up alerts.¿ Build custom dashboards to accurately display key financial metrics.WHO THIS BOOK IS FORThis book is for cloud architects, DevOps engineers and IT professionals managing costs in Azure environments. It provides the necessary knowledge and skills to optimize cloud spending, improve efficiency, and drive business value.

DESCRIPTION Honeypots are like digital traps designed to lure malicious attackers away from your real systems. Imagine setting up a fake store to attract thieves while your real store is safe and hidden. Honeypots work in a similar way, drawing the attention of cybercriminals and allowing you to study their tactics and potentially prevent future attacks.This book simplifies the concept of honeypots, which are important tools in cybersecurity. The book explains their history, types, and how to design and use them effectively. It includes practical advice on setting up honeypots, monitoring them, and analyzing attacks. It also offers strategies for blue team professionals, like SOC analysts, to improve defenses and serves as a helpful resource for purple team members to practice detecting attacks. Additionally, it discusses how honeypots contribute to threat intelligence and cybersecurity training, including new ideas like quantum honeypots, preparing professionals to face modern cyber threats.By the end of this book, you will be able to effectively deploy and manage honeypots, analyze attack data, and implement strategies to protect your organization from malicious attacks.KEY FEATURES ¿ Design and deployment of honeypot to trap hackers.¿ Step-by-step guide for implementation with best practices.¿ Quantum insights and threat anticipation for future-proof defense.WHAT YOU WILL LEARN¿ Acquire an understanding of honeypot technology, from foundational concepts to advanced techniques.¿ Learn how to design and implement honeypots tailored to specific security needs and threat landscapes.¿ Effectively monitor and analyze honeypot data to detect and respond to attacks.¿ Explore advanced honeypot techniques, such as honeypot farms and distributed honeypot networks.WHO THIS BOOK IS FORThis book is a vital resource for CTOs, CISOs, InfoSec managers, InfoSec analysts, and network admins. This book will help students and researchers who are working in the domain of cybersecurity.

DESCRIPTION Kotlin, a modern and expressive language, has revolutionized Android app development. As the app complexity grows, building scalable and maintainable Android apps becomes crucial. This book is a complete guide to modern Android app development using Kotlin. It covers key concepts like clean architecture and dependency injection for building strong, maintainable apps. This book will also help you learn how to use Kotlin DSL for build configuration and Jetpack Compose for creating user interfaces. It also covers testing, debugging, networking, and API integration. With best practices and real-world examples, this book will help developers create high-quality Android apps using Kotlin.By the end of this book, you will be equipped with the knowledge and skills to architect, develop, and deploy scalable Android apps using Kotlin. You will confidently tackle complex app development challenges, write clean, efficient, and testable code, and become a proficient Android developer.WHAT YOU WILL LEARN¿ Kotlin and Jetpack Compose fundamentals.¿ Feature-oriented separation of concerns.¿ Clean-code architecture in Android.¿ Kotlin-specific test-driven development.¿ Multi-module project organization.¿ Tips and techniques for debugging.¿ Continuous integration and releasing applications.WHO THIS BOOK IS FORThis book can be understood by novice developers but will also benefit intermediate/seasoned professionals in the Android space. This book is a must-have for Android developers, software engineers, and mobile app developers striving to create exceptional applications.

DESCRIPTION Streamlit Essentials is a comprehensive guide aimed at helping you build interactive data applications using Python. With easy-to-use syntax, it allows developers to quickly build visualizations, dashboards, and machine learning models.This book is a practical guide to building data science applications using the Streamlit framework. It covers everything from installation to advanced topics like ML integration and deployment. With real-world projects and examples, you will learn how to use Streamlit's widgets, styling, and data visualization tools to create dynamic real-time dashboards, containerize your applications with Docker, securely handle sensitive data, and deploy the applications on leading cloud platforms, all while building practical projects that can be added to enhance your portfolio.Throughout the book, you will develop the skills needed to turn data insights into interactive visualizations, ensuring your projects are not only functional but also engaging. The focus is hands-on learning, with step-by-step guidance to help you build, optimize, and share your work. By the time you have completed this book, you will be able to confidently deploy applications, showcase your skills through a professional portfolio, and position yourself for success. WHAT YOU WILL LEARN¿ Understanding of Streamlit's capabilities, from its core functionalities to advanced features.¿ Create engaging and informative visualizations using Streamlit's extensive library of charts, graphs, and maps.¿ Develop efficiently using time-saving techniques for rapid prototyping and iterative development.¿ Optimize app performance with advanced topics like caching, session tracking, and theming.¿ Create a compelling portfolio to demonstrate your Streamlit proficiency.WHO THIS BOOK IS FORWhether you are a data scientist, analyst, developer, or business professional, this book will provide you with the knowledge and skills needed to build engaging and informative dashboards, visualizations, and ML models.

DESCRIPTION Java is a versatile programming language, ideal for scientific computing due to its robustness, platform independence, and extensive libraries. This book teaches you how to use Java for complex simulations and data analysis, empowering you to solve real-world problems and advance scientific research.This Java programming book offers a thorough guide, starting with core concepts like data types, operators, and object-oriented programming (OOP). It then moves into advanced topics such as multithreading for handling multiple tasks at once, exception handling to manage runtime errors, and package management for organizing large codebases. You will also learn about input/output (I/O) operations to work with external data and applet development for creating small, interactive web programs. Building on your knowledge of Java programming and scientific computing, this book is a complete guide that equips you to delve into scientific computing and actively participate in innovative research and development.KEY FEATURES ¿ Learn Java's data structures, algorithms, and numerical libraries.¿ Practical examples and exercises to solidify understanding.¿ MCQs with solutions are provided at the end of each chapter for practice, along with Bloom's level questions.¿ Miscellaneous programs using Java, like Stack, Queue, Tic-tac-toe, AES, and RSA algorithms, and socket programming, are also included.WHAT YOU WILL LEARN¿ Understand and code with data types, variables, arrays, and strings.¿ Learn iterations, conditional statements, and how to apply them.¿ Explore OOP with examples.¿ Master multithreading for multi-tasking environments.¿ Grasp Java exception handling and file management.WHO THIS BOOK IS FORThis book is ideal for professionals in fields such as software development, data analysis, web development, and system administration who need a strong foundation in Java programming.

DESCRIPTION As an engineer, it can feel like there is never enough time for testing, designing, or delivering quality solutions. Managers often feel overwhelmed by the need to deliver new features to support their teams while managing vulnerabilities and security standards. Engineers often have to work with legacy systems and learn many new technologies simultaneously to be effective in their jobs. This book teaches you continuous modernization, a key skill for tackling modern and legacy software. By adopting the right mindset and techniques, you will improve systems and workflows, making everything more efficient over time.Continuous modernization is your essential guide to updating old software systems into modern, efficient, and scalable applications. This book covers everything from changing your mindset and technical practices to business strategies and fostering a culture of innovation. It includes tips on unlearning outdated methods, embracing feedback, making smart decisions, ensuring stability, and applying modern design principles. With practical techniques and real-world examples, it provides the tools you need to modernize your software systems and achieve lasting success successfully.By the end of this book, readers will master continuous modernization principles and practices. They will learn to spot areas needing improvement, create effective modernization strategies, and implement changes that boost value and efficiency. Additionally, they will understand how to build a culture of innovation and ongoing learning to keep their software systems up-to-date and competitive in a fast-changing tech world.WHAT YOU WILL LEARN¿ Learn patterns, anti-patterns, and tools to improve software architecture decisions.¿ Eliminate limiting practices to improve development efficiency.¿ Apply disciplined feedback loops to refine architecture and design decisions.¿ Implement advanced troubleshooting techniques to prevent design flaws.¿ Continuously refactor systems and scale modernization efforts in distributed architectures.WHO THIS BOOK IS FOROur book is for professionals in the field of computer science. It is for software architects, engineers, testers, managers, directors, and VPs. This is for individuals and teams who may or may not have a modernization project but care about improving individuals and systems daily.

DESCRIPTION In today's data-driven world, the ability to extract meaningful insights from vast datasets is crucial for success in various fields. This ultimate book for mastering open-source libraries of data science in Python equips you with the essential tools and techniques to navigate the ever-evolving field of data analysis and visualization.Discover how to use Python libraries like NumPy, Pandas, and Matplotlib for data manipulation, analysis, and visualization. This book also covers scientific computing with SciPy and integrates ChatGPT to boost your data science workflow. Designed for data scientists, analysts, and beginners, it offers a practical, hands-on approach to mastering data science fundamentals. With real-world applications and exercises, you will turn raw data into actionable insights, gaining a competitive edge. This book covers everything you need, including open-source libraries, Visual Explorer tools, and ChatGPT, making it a one-stop resource for Python-based data science.Readers will gain confidence after going through this book and we assure you that all the minute details have been taken into consideration while delivering the content. After reading, learning, and practicing from this book, we are sure that all IT professionals, novices, or job seekers will be able to work on data science projects thus proving their mettle.WHAT YOU WILL LEARN¿ Learn to work with popular IDEs like VS Code and Jupyter Notebook for efficient Python development.¿ Master open-source libraries such as NumPy, SciPy, Matplotlib, and Pandas through advanced, real-world examples.¿ Utilize automated EDA tools like PyGWalker and AutoViz to simplify complex data analysis.¿ Create sophisticated visualizations like heatmaps, FacetGrid, and box plots using Matplotlib and Seaborn.¿ Efficiently handle missing data, outliers, and perform filtering, sorting, grouping, and aggregation using Pandas and Polars.WHO THIS BOOK IS FORThis book is ideal for diploma, undergraduate, and postgraduate students from engineering and science fields to programming and software professionals. It is also perfect for data science, ML, and AI engineers looking to expand their expertise in cutting-edge technologies.

DESCRIPTION Cybersecurity mesh architecture (CSMA) is a new way to protect your data. It connects all your security tools together, making them work better as a team. This book will teach you everything you need to know about CSMA, from how it works to how to use it to protect your business.The book introduces the current cybersecurity landscape, explaining CSMA and its key components, benefits, and adoption strategies. It covers best practices, implementation challenges, and key performance indicators (KPIs) for evaluating CSMA effectiveness. Additionally, it compares CSMA with traditional defense methods, detailing its advantages. The book also explores its specific applications in the healthcare sector. It provides valuable insights into the CSMA market, including growth factors, dynamics, and emerging opportunities for businesses looking to enhance their cybersecurity posture.By the end of this book, you will gain a deep understanding of CSMA and its potential to revolutionize your organization's cybersecurity posture. You will be equipped with the knowledge and skills to implement CSMA effectively, safeguarding your data and mitigating risks in the face of ever-evolving threats.WHAT YOU WILL LEARN¿ Foundational concepts of cybersecurity and the challenges faced by traditional systems.¿ Explore the complexities of distributed systems and the human factor in cybersecurity.¿ Understand the building blocks for a resilient cybersecurity architecture and the benefits of emerging trends like 5G, XDR, and Zero Trust.¿ Learn how to effectively adopt CSMA, transitioning from siloed systems to a unified architecture.¿ Discover the advantages of CSMA, including improved visibility, reduced complexity, and enhanced automation.WHO THIS BOOK IS FORThis book is for CIOs, CISOs, security architects, engineers, and operations professionals working in enterprise security or networking teams. It is also ideal for threat hunters, endpoint security specialists, and students studying cybersecurity who have a basic knowledge of cybersecurity, cloud, and networking challenges.

DESCRIPTION Qlik Sense is a powerful business intelligence tool that helps organizations make data-driven decisions. It is widely used by businesses of all sizes to visualize and analyze data to gain insights into their operations.This book is a detailed guide to Qlik Sense, a top business intelligence tool. It covers BI basics, data modeling, visualization, and advanced analysis techniques. Learn to create dashboards, explore data associations, and share insights through stories and annotations. The book also offers guidance on managing and securing your Qlik Sense environment, with tips on troubleshooting and backups, ensuring effective use for data-driven decisions. By the end of the book, readers will have a deep understanding of Qlik Sense and the ability to use it to solve complex business problems. Readers will learn how to use data visualization and analytics to make informed business decisions, as well as how to build effective data models and create data stories that communicate insights effectively. WHAT YOU WILL LEARN¿ Master Qlik Sense architecture, environment setup, and application creation.¿ Create advanced data visualizations with interactive charts and dashboards.¿ Implement efficient data modeling, optimization, and performance tuning.¿ Build NPrinting reports and mashups for enhanced data reporting.¿ Manage user access, security, and governance for Qlik Sense environments.WHO THIS BOOK IS FORThis book is designed for business professionals, data analysts, IT professionals, and students who want to learn how to use Qlik Sense for data analysis and visualization. The book is suitable for readers with any level of experience using Qlik Sense, from beginners to advanced users.