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Master data analysis with Python in this comprehensive guide, covering everything from cleaning datasets to visualizing data.

Key Features

Step-by-step explanations for all key conceptsPractical examples and hands-on exercisesComprehensive coverage of data analysis, statistics, and visualization

Book Description

This book ushers readers into the world of data, emphasizing its importance in modern industries and how its management leads to insightful decision-making. Using Python 3, the book introduces foundational data tasks and progresses to advanced model training concepts. Detailed, step-by-step Python examples help readers master training models, starting with the kNN algorithm and moving to other classifiers with minimal code adjustments. Tools like Sweetviz, Skimpy, Matplotlib, and Seaborn are introduced for hands-on chart and graph rendering.The course begins with working with data, detecting outliers and anomalies, and cleaning datasets. It then introduces statistics and progresses to using Matplotlib and Seaborn for data visualization. Each chapter builds on the previous one, ensuring a comprehensive understanding of data management and analysis.These concepts are crucial for making data-driven decisions. This book transitions readers from basic data handling to advanced model training, blending theoretical knowledge with practical skills. Companion files with source code and data sets enhance the learning experience, making this book an invaluable resource for mastering data science with Python.

What you will learn

Understand the basics of data literacyIdentify and handle outliers and anomaliesClean and preprocess datasetsApply statistical methodsVisualize data using Matplotlib and SeabornUtilize Python and Pandas for data analysis

Who this book is for

This book is ideal for beginners and intermediate data analysts, data scientists, and Python programmers. A basic understanding of Python is recommended but not required, as the book includes an introduction to Python. No prior knowledge of data analysis is necessary, making it accessible to anyone interested in data literacy.

Unlock the power of data visualization to make informed business decisions with this comprehensive guide. Learn practical techniques to turn data into actionable insights.

Key Features

Practical exercises and case studies to enhance learningFocus on storytelling and sign-making to improve data communicationComprehensive coverage of perception principles and chart selection methods

Book Description

This workbook is for business analysts aiming to enhance their skills in creating data visuals, presentations, and report illustrations to support business decisions. It focuses on developing visualization and analytical skills through qualitative labs. Readers will analyze and describe chart improvements instead of directly modifying them. The course covers eighteen elements across six dimensions: Story, Signs, Purpose, Perception, Method, and Charts.The journey starts with labs and a case study, introducing the analysis tool. It then delves into each dimension, guiding readers through exercises to enhance their understanding and skills. A comprehensive RAIKS survey assesses progress before and after using the text. The workbook concludes with a capstone exercise to review and analyze the final results of the two studied charts.These skills are crucial for effective data communication in business. This workbook transitions readers from basic to advanced visualization techniques, blending theoretical insights with practical skills. Companion files with videos, sample files, and slides enhance learning, making this workbook an essential resource for mastering business data visualization.

What you will learn

Create effective data visualizationsAnalyze case studiesUtilize storytelling techniquesDesign with purposeUnderstand perception principlesSelect appropriate charts

Who this book is for

This book is ideal for business professionals, analysts, and decision-makers seeking to improve their data visualization skills. A basic understanding of data analysis and familiarity with business concepts are recommended.

Master data science tools like R, Excel, KNIME, and OpenOffice with hands-on examples and practical applications.

Key Features

Step-by-step instructions for using R, Excel, KNIME, and OpenOffice.Comprehensive coverage of statistical tests and methods.Real-world examples to apply the concepts learned.

Book Description

This book introduces popular data science tools and guides readers on how to use them effectively. It covers data analysis using Microsoft Excel, KNIME, R, and OpenOffice, applying statistical concepts such as confidence intervals, normal distribution, T-Tests, linear regression, histograms, and geographic analysis with real data from Federal Government sources.The course begins with the basics, including importing data and conducting various statistical tests. It progresses to specific methods for each tool, ensuring a comprehensive understanding of data analysis. Capstone exercises provide hands-on experience, reinforcing the concepts learned throughout the book.Understanding these tools and concepts is crucial for effective data analysis. This book takes readers from the basics to advanced statistical methods, combining theoretical insights with practical applications. Companion files with source code and data sets enhance the learning experience, making this book an essential resource for mastering data analysis with popular software applications.

What you will learn

Import data using Excel, OpenOffice, R, and KNIME.Conduct statistical tests and analyses.Utilize specific statistical methods for each tool.Create data visualizations.Perform random sampling and power analysis.Apply Benford''s Law and create word clouds.

Who this book is for

This book is ideal for data science enthusiasts, students, and professionals looking to enhance their skills with popular tools like R, Excel, KNIME, and OpenOffice. A basic understanding of data analysis concepts is recommended but not required, as the book provides foundational knowledge and progresses to advanced topics.

Master the art of programming with flowcharts and algorithms. Learn step-by-step from basic concepts to advanced topics through practical exercises.

Key Features

Comprehensive introduction to flowcharts and algorithmsPractical exercises to reinforce learningCovers selection, looping, arrays, and file processing techniques

Book Description

This book equips readers with efficient, well-structured program logics using flowcharts and algorithms. Flowcharting helps create sequences of steps to solve problems through arithmetic and logical manipulations, essential for instructing computers. Applied examples from various subjects encourage readers to grasp the logic leading to solid programming basics.The course begins with an introduction to programming, moving on to problems involving selection, looping, and arrays. It concludes with the art of file processing. Each chapter builds on the previous one, ensuring a comprehensive understanding of programming logic and flowcharting techniques.Understanding these concepts is crucial for developing effective computer instructions. This book transitions readers from basic to advanced problem-solving skills, combining theoretical knowledge with practical examples. It is an essential resource for mastering programming logic and flowcharting.

What you will learn

Understand the fundamentals of programmingCreate and interpret flowchartsDevelop algorithms to solve problemsApply selection and looping conceptsWork with arrays effectivelyMaster file processing techniques

Who this book is for

The ideal audience for this book includes beginner and intermediate programmers, computer science students, and anyone interested in learning programming fundamentals. Readers should have a basic understanding of computer operations. No prior programming experience is required, making it suitable for those starting their programming journey.

Learn 3D graphics programming with OpenGL and Java using this comprehensive guide. Covering everything from basic setup to advanced topics like ray tracing and VR, this book is ideal for students and professionals.Key FeaturesComprehensive guide from basic to advanced 3D graphics programming.Hands-on approach with complete programming examples.Covers advanced topics such as ray tracing and VR.Book DescriptionThis book is designed for computer science undergraduates and professionals interested in mastering 3D graphics using OpenGL in Java with JOGL. It follows a "e;teach-yourself"e; format with numerous examples that can be run as presented. Unique in its approach, it covers OpenGL 4.0+ shader programming using Java, providing all the necessary materials to install JOGL and execute every example. The course starts with an introduction to OpenGL and the graphics pipeline, followed by mathematical foundations essential for 3D graphics. It then delves into managing 3D graphics data, texture mapping, and creating 3D models. Lighting, shadows, and enhancing surface detail are covered, along with advanced techniques like parametric surfaces, tessellation, and geometry shaders. The final chapters explore simulating water, ray tracing, and stereoscopy for 3D glasses and VR headsets. This book equips readers with comprehensive skills in OpenGL programming and 3D graphics, making it an invaluable resource for developing sophisticated graphics applications. The practical approach ensures thorough learning, bridging the gap between theory and application.What you will learnInstall and configure Java and OpenGL libraries.Implement the OpenGL graphics pipeline in Java.Build and animate 3D objects and scenes.Apply mathematical foundations for 3D graphics.Manage textures, lighting, and shadows.Simulate water and implement ray tracing and VR.Who this book is forIdeal for computer science students, both undergraduate and graduate, as well as professionals looking to enhance their knowledge of 3D graphics programming. Readers should have a solid background in object-oriented programming and basic understanding of linear algebra and trigonometry.

Master essential business mathematics skills with comprehensive explanations and practical examples. Perfect for business professionals and students.

Key Features

Comprehensive coverage of business math topicsPractical examples and exercises in each chapterClear explanations of complex concepts

Book Description

This book is designed for students, faculty, and professionals, describing the role of mathematics in economics and business. Starting with the basics of numbers and advancing into complex topics like hyperreal numbers and set theory, the book builds a strong foundation of mathematical concepts. Python code is used throughout to illustrate problems numerically, making the material accessible and practical.Readers will learn about linear simultaneous equations for market equilibrium analysis and the mechanics of matrices for solving larger systems. The book covers calculus, with applications in economics, including profit maximization and factor optimization, and introduces infinitesimal methods. Chapters on differential and difference equations reveal their importance in analyzing dynamic systems, all illuminated through practical examples and images from economics and business.The course begins with fundamental mathematical concepts, advancing to complex applications in economics and business. By integrating computational understanding with Python code, the book ensures learners can tackle real-world problems. This structured approach provides the tools needed for economic analysis and business decision-making, making it an invaluable resource for anyone in these fields.

What you will learn

Understand sets, numbers, and algebraic rulesApply calculus in business contextsSolve simultaneous equationsOptimize multivariable functionsUtilize matrix algebraApproach differential equations methodically

Who this book is for

This book is ideal for business students, professionals in finance and economics, and anyone looking to enhance their analytical skills. Basic knowledge of high school mathematics is recommended, but the book provides thorough explanations and exercises for deeper understanding.

A comprehensive guide to mastering data structures and program design using Python, perfect for self-learners and students alike.

Key Features

Hands-on exercises to reinforce learningComprehensive coverage of fundamental and advanced topicsPractical examples to apply concepts in real-world scenarios

Book Description

This book, part of the Pocket Primer series, introduces the basic concepts of data science using Python 3 and other applications. It offers a fast-paced introduction to data analytics, statistics, data visualization, linear algebra, and regular expressions. The book features numerous code samples using Python, NumPy, R, SQL, NoSQL, and Pandas. Companion files with source code and color figures are available.Understanding data science is crucial in today''s data-driven world. This book provides a comprehensive introduction, covering key areas such as Python 3, data visualization, and statistical concepts. The practical code samples and hands-on approach make it ideal for beginners and those looking to enhance their skills.The journey begins with working with data, followed by an introduction to probability, statistics, and linear algebra. It then delves into Python, NumPy, Pandas, R, regular expressions, and SQL/NoSQL, concluding with data visualization techniques. This structured approach ensures a solid foundation in data science.

What you will learn

Understand the basics of data structuresLearn Python programming essentialsImplement and manipulate various data structuresAnalyze algorithms and their efficiencyLearn about arrays, trees, linked lists, stacks, etc.Apply data structures to solve real-world problems

Who this book is for

Ideal for students, self-learners, and programming enthusiasts, this book requires a basic understanding of programming concepts. No prior knowledge of Python is needed as the book covers Python essentials.

Learn Java programming through game development, covering basics to advanced concepts with practical examples.

Key Features

Use of game programming to teach Java concepts, making learning engaging and interactiveA wide range of topics from basic programming to advanced Java features, ensuring comprehensive learningPractical examples and exercises, reinforcing learning through hands-on practice

Book Description

This Java-based book is designed for beginning programmers, using game programming as a central tool to enhance student engagement and learning outcomes. The new edition updates GUI interface chapters from Swing to FX-based programs. The game programming integration does not compromise the traditional programming material, allowing instructors unfamiliar with game programming to leverage its pedagogical benefits. The book assumes no prior programming experience.Starting with an introduction, the course progresses through variables, input/output, calculations, methods, classes, objects, boolean expressions, and decision-making. It then covers loops, arrays, advanced object-oriented concepts, inheritance, recursion, and exceptions. The latter part focuses on graphical user interfaces, generics, the API collection framework, multithreading, and concurrency.By the end of the course, students will have a comprehensive understanding of Java programming, enhanced by practical game programming applications. This approach not only makes learning more engaging but also provides a solid foundation for more advanced Java programming concepts.

What you will learn

Understand the basics of Java programmingCreate and manipulate variablesDevelop graphical user interfacesImplement object-oriented programming conceptsApply data structures and algorithmsHandle multithreading and concurrency

Who this book is for

This book is ideal for students and professionals interested in learning Java through game development. A basic understanding of programming is recommended, but not required, as the book starts with fundamental concepts and gradually moves to advanced topics. No prior experience with game programming or Java is necessary.

Master Excel VBA with hands-on examples. Automate tasks, manipulate data, and customize your Excel experience effortlessly.

Key Features

Detailed examples and practical applications of VBA programmingStep-by-step instructions for automating tasks and data analysisAdvanced techniques for user interface customization and file manipulation

Book Description

Updated for Excel 2021, this book is a practical guide for those proficient with the Excel user interface and looking to automate routine tasks. It introduces programming concepts through numerous hands-on exercises, progressing to advanced topics via custom projects. The journey begins with recording and editing macros, writing VBA code, and extends to programming the Ribbon interface and working with XML documents. The course covers automating operations on files, folders, and other Microsoft Office applications. It also delves into event procedures, testing, and debugging. Advanced features include working with VBA classes and raising custom events in standalone class modules. By mastering these skills, users can significantly enhance their productivity and efficiency in Excel.The book''s structure, with 29 chapters and over 275 examples, ensures comprehensive learning. Companion files with source code, projects, and figures further support the user. This course is essential for anyone aiming to streamline their Excel tasks and harness the full power of Excel programming.

What you will learn

Write effective Excel MacrosAutomate repetitive tasksUse advanced data analysis techniquesInteract with other applicationsCustomize the Excel interfaceManipulate files and folders

Who this book is for

Ideal for Excel users, data analysts, and anyone looking to automate repetitive tasks or enhance their Excel skills. No prior programming experience is required, but basic Excel knowledge is recommended. Suitable for both beginners and advanced users.

Dive into the world of AI and expert systems with this comprehensive guide, covering everything from foundational concepts to advanced applications.Key FeaturesComprehensive coverage of AI and expert systems from basics to advanced topicsPractical examples and detailed explanations for hands-on learningLogical progression of chapters to build a solid understandingBook DescriptionAs part of the Pocket Primer series, this book introduces basic deep learning concepts and integrates them into Angular 10 applications. It offers a fast-paced introduction to deep learning features and popular classifiers. Covering Angular 10 functionality, deep learning concepts, and key classification algorithms, the book includes code samples and figures. Topics such as TensorFlow and Keras are also explored. The book begins with an introduction to AI and its applications, followed by state space search and heuristic search strategies. You will delve into expert systems, their development life cycle, knowledge acquisition, and representation. These topics lead to a deeper understanding of neural networks, the learning process, and fuzzy logic systems, ensuring a comprehensive grasp of AI and deep learning principles. Understanding these concepts is essential for developing sophisticated AI applications and enhancing Angular 10 projects. This book transitions you from a novice to a proficient developer, equipped with practical skills and knowledge. Advanced topics like fuzzy expert systems and logic programming are covered, culminating in advanced Prolog. Companion files with source code and color figures enhance the learning experience, making this book an invaluable resource for integrating deep learning with Angular 10.What you will learnUnderstand the foundational concepts of AIApply heuristic search strategies effectivelyDevelop and implement expert systemsUtilize neural networks for machine learningLeverage fuzzy logic in decision-makingMaster programming in PrologWho this book is forThis book is ideal for software engineers, data scientists, and IT professionals seeking to deepen their understanding of AI and expert systems. Readers should have a basic understanding of programming and computer science principles. Prior experience with AI or machine learning concepts is beneficial but not required.

Dive into the essentials of AI with this self-teaching guide, covering problem representation, search processes, game playing, knowledge representation, and more. Perfect for beginners and enthusiasts alike.Key FeaturesIn-depth introduction to AI concepts and applicationsPractical exercises and review questions for hands-on learningCovers both theoretical foundations and practical programming aspectsBook DescriptionThis book is designed as a self-teaching introduction to the fundamental concepts of artificial intelligence (AI). It begins with the history of AI, the Turing test, and early applications, providing a strong foundation. Later chapters cover the basics of searching, game playing, and knowledge representation. The journey continues with detailed explorations of expert systems and machine learning, equipping readers with essential AI techniques. As the course progresses, you will delve into separate programming chapters on Prolog and Python, learning how to implement AI concepts in these languages. These chapters offer practical coding experience, enhancing your understanding of AI programming. The book culminates with a comprehensive chapter on AI machines and robotics, showcasing numerous modern applications and providing a glimpse into the future of AI technology. Understanding these AI concepts is crucial as they form the basis of many modern technologies and applications. This book ensures a smooth transition from a beginner to a proficient AI practitioner, equipped with both theoretical knowledge and practical skills. By the end of the book, you will have a thorough understanding of AI's history, core principles, and practical implementations, ready to apply this knowledge to real-world problems and projects.What you will learnUnderstand the fundamentals of AILearn problem representation techniquesExplore search processesStudy game-playing algorithmsGrasp knowledge representation methodsGet introduced to Prolog and Python for AIWho this book is forIdeal for beginners in AI, computer science students, and tech enthusiasts. Prior knowledge of basic programming concepts is helpful but not required. Readers should be familiar with general computer usage and have an interest in AI and machine learning.

Master 3D graphics programming with OpenGL and C++, covering everything from basic concepts to advanced techniques.Key FeaturesComprehensive coverage of 3D graphics programming with OpenGLPractical examples and hands-on tutorialsFocus on advanced techniques and real-world applicationsBook DescriptionThis edition provides step-by-step instruction on modern OpenGL 4.0+ GLSL shader programming with C++, covering theoretical foundations of 3D computer graphics. Every shader stage is explored, from basics like modeling, textures, lighting, and shadows, to advanced techniques such as tessellation, noise maps, water, and stereoscopy. Expanded coverage includes camera control, refraction, and ray tracing with bounding volume hierarchies. Companion files include source code, shaders, model files, and skyboxes for all examples in the book. Understanding these concepts is crucial for creating sophisticated 3D graphics applications. The course begins with OpenGL basics and pipeline understanding, followed by mathematical foundations and managing 3D graphics data. It covers texture mapping, 3D models, lighting, shadows, enhancing surface detail, and advanced topics like parametric surfaces, tessellation, and geometry shaders. Final chapters delve into simulating water, ray tracing, and stereoscopy for 3D graphics. This book equips readers with the knowledge to master OpenGL programming and 3D graphics, making it invaluable for developers and enthusiasts aiming to advance their skills. The practical approach and comprehensive examples ensure thorough learning, bridging the gap between theory and real-world application.What you will learnUnderstand OpenGL graphics pipelineApply mathematical foundationsManage 3D graphics dataImplement texture mapping and lightingUse advanced techniques like tessellation and ray tracingSimulate realistic environments and effectsWho this book is forAspiring graphics programmers, computer science students, and developers looking to enhance their skills in 3D graphics. Basic knowledge of C++ is required, while familiarity with OpenGL is beneficial.

Master the stock market with practical strategies for buying, selling, and managing AI risks. This guide covers fundamental and technical analysis, sector analysis, and AI tools.

Key Features

Comprehensive guide to stock market investingPractical strategies for buying and selling stocksIn-depth coverage of AI tools for risk management

Book Description

This book is perfect for investors, financial analysts, and portfolio managers. It simplifies stock market investing, offering strategies and practical advice for all levels. Key topics include research, buying and selling strategies, and using AI for risk management. The book equips you with essential knowledge and tools for successful stock investing.The course begins with planning, research, and screening, then moves to buying strategies and identifying winning characteristics. It covers company and sector analysis, selling techniques, stock prices, valuation, profitability, market behavior, and technical analysis. Advanced topics include monitoring the economy, market indicators, and avoiding investment mistakes.Understanding these concepts is crucial for informed investment decisions. The final chapters focus on risk management and leveraging AI in stock investing, addressing AI risks and mitigation strategies. This book guides readers from basic to advanced stock market concepts, blending theory with practical skills, making it essential for mastering stock investing.

What you will learn

Plan and execute effective investment strategiesAnalyze companies and sectors thoroughlyImplement technical and fundamental analysisUtilize AI for risk management and investment decisionsAvoid common investing and trading mistakesMonitor economic indicators and market trends

Who this book is for

Ideal for individual investors, traders, and finance professionals seeking to improve their stock market skills. This book is suitable for those with a basic understanding of investing and looking to deepen their knowledge of fundamental and technical analysis, as well as AI-driven risk management. No advanced prerequisites are required.

Learn Adobe InDesign from scratch with this beginner-friendly guide. Step-by-step projects help you create professional designs for web and print.Key FeaturesComprehensive guide for beginners to master Adobe InDesignStep-by-step practical projects for hands-on learningIntegration of other Adobe programs for advanced design workBook DescriptionThis book explores digital design, tailored for beginners eager to master Adobe InDesign, and serves as a valuable resource for experienced users refining their skills. It demystifies Adobe InDesign, defining essential tools through engaging projects and tutorials. Starting with navigating the interface, it lays a solid foundation by teaching how to open and create documents, understand the workspace, and tailor the program to individual needs. The book offers practical experience with projects such as web banners, social media ads, logos, flyers, posters, covers, newsletters, and booklets. Each project builds on the previous one, ensuring a comprehensive understanding of InDesign's capabilities. A complete Save the Sharks marketing campaign allows users to apply their skills in a real-world context, with options to customize content for personal campaigns. Understanding Adobe InDesign is crucial for creating professional-quality designs. This book transitions users from novices to confident designers, equipped with practical skills and comprehensive knowledge. It ensures a smooth learning journey, enhancing creative potential and proficiency in digital design. Companion files with video tutorials and project files enrich the learning experience, making it an essential resource for all levels.What you will learnNavigate the Adobe InDesign workspaceCreate and customize documentsDesign web and print mediaDevelop presentation materialsRework and improve design projectsIncorporate other software toolsWho this book is forBeginners to Adobe InDesign will find this book ideal, especially those looking to create professional designs for web and print. No prior knowledge of InDesign is required, but basic computer skills are helpful. The book serves as a comprehensive guide from fundamentals to advanced project work.

Explore vector spaces, transformations, and matrix decompositions with practical applications in coding and image processing.

Key Features

In-depth theoretical conceptsPractical applications and exercisesComprehensive coverage of linear algebra topics

Book Description

This book introduces the fundamental concepts of linear algebra and applies the theorems in computation-oriented applications. It is suitable for a one-semester course and combines definitions and proofs with a focus on computational applications. Examples illustrate the use of software packages such as Mathematica, Maple, and Sage.The journey begins with vector spaces and progresses through linear transformations and operators. It then covers orthogonal bases and matrix decomposition. The material includes a brief introduction to aspects of abstract algebra related to linear algebra, such as groups, rings, modules, fields, and polynomials over fields.Understanding these concepts is crucial for solving complex problems in various fields. This book transitions readers from basic definitions to advanced computational applications, blending theoretical knowledge with practical skills. It is an essential resource for mastering linear algebra and its applications.

What you will learn

Understand vector spacesPerform linear transformationsSolve linear equationsDecompose matricesApply orthogonal basesUse linear algebra in coding

Who this book is for

Ideal for students, educators, and professionals in mathematics, computer science, and engineering. Readers should have a basic understanding of algebra. No advanced prerequisites are necessary.

Master grep, sed, and awk with this practical pocket primer. Learn through hands-on examples and clear explanations designed for both beginners and experienced users.

Key Features

Learn grep, sed, and awk from basics to advancedPractical examples and clear explanationsComprehensive coverage for both beginners and experienced users

Book Description

This book introduces readers to three powerful command-line utilities—grep, sed, and awk—that can create simple yet powerful shell scripts. Using the bash shell, it focuses on small text files to help readers understand these tools. Grep searches for patterns in data, sed modifies data, and awk performs tasks on pattern matches. Aimed at those new to the bash environment, the book is also valuable for those with some experience.The journey starts with grep, teaching how to search for specific words or patterns in data. It then moves to sed, showing how to change or modify data efficiently. Finally, it delves into awk, a versatile programming language for searching and processing data files. The book also includes a chapter on using regular expressions with these tools, enhancing your scripting capabilities.Mastering these utilities is crucial for efficient data handling and automation in a bash environment. This book transitions readers from basic to advanced command-line skills, blending theory with practical examples. It is an essential resource for anyone looking to harness the full power of bash scripting.

What you will learn

Understand the basics of grepUtilize sed for text substitutionLeverage awk for data extractionCombine commands for complex tasksUse regular expressions effectivelyApply learned skills in real-world scenarios

Who this book is for

Ideal for anyone wanting to perform various tasks from the command line, this book is suitable for beginners and those with some command line experience. A basic familiarity with Unix-like environments is beneficial but not required. The book caters to general users, data scientists, developers, and IT professionals.

Master network security and cryptography with this in-depth guide covering essential concepts, techniques, and advanced topics for protecting data and networks.

Key Features

Comprehensive coverage of network security and cryptographyPractical encryption and decryption techniquesSecurity of emerging technologies like IoT and blockchain

Book Description

This new edition introduces fundamental concepts in computer networks, blockchain, cryptography, and network security. It covers classical cipher schemes, public key cryptography, authentication schemes, and Internet security, featuring new material on IoT, cloud computing, SCADA, blockchain, smart grid, big data analytics, and AI security.Starting with computer network basics and mathematical foundations, it then explores classical and modern cipher schemes, public-key cryptography, and authentication methods. Later chapters address Internet and system security, and emerging technologies.Intended as a textbook for computer science and electronics courses, it also serves as a comprehensive reference for professionals. Its structured approach ensures a thorough understanding of both foundational and advanced topics, making it essential for mastering cryptography and network security.

What you will learn

Understand the OSI and TCP/IP modelsImplement symmetric and asymmetric encryptionApply cryptographic protocols and algorithmsUtilize modern cryptographic systemsSecure emerging technologiesLeverage AI for intrusion detection

Who this book is for

This book is ideal for cybersecurity professionals, network administrators, and IT students seeking to enhance their knowledge of network security and cryptography. A basic understanding of computer networks is recommended.

Master Blazor and WebAssembly with practical examples and in-depth explanations. This comprehensive guide covers everything from basic Blazor components to advanced deployment techniques using Docker and Kubernetes.

Key Features

A comprehensive coverage of core and advanced Blazor concepts, including WebAssemblyPractical examples and source code analysis for hands-on learningExploration of modern deployment techniques using Docker and Kubernetes

Book Description

Web Applications with ASP.NET Core Blazor is a comprehensive guide to building modern web applications using the Blazor framework. It begins with an introduction to WebAssembly, detailing its purpose, history, and integration with JavaScript, followed by an exploration of Blazor''s various hosting models, including Blazor Server, Blazor WebAssembly, and Blazor Hybrid.The book covers essential Blazor components like Razor, directives, data binding, and event handling, and delves into advanced component techniques such as CSS isolation and component templating. Readers will also learn about file uploading, serving, and securing files within Blazor applications.The text provides thorough insights into user input collection through forms, navigation in Blazor apps, and interop between .NET and JavaScript. Additionally, it explores HTTP communication, data persistence using EF Core, and security measures with Identity.Finally, the book concludes with a deep dive into deploying Blazor applications using Docker and Kubernetes, including practical guidance on containerization and deploying on Azure. Designed for web developers and tech enthusiasts, this book equips readers with the knowledge to build robust, interactive web applications with ASP.NET Core Blazor.

What you will learn

Master the basics of Blazor components and directivesExplore advanced Blazor component featuresImplement file uploading and serving securelyIntegrate .NET and JavaScript seamlesslyPersist data using EF CoreDeploy applications with Docker and Kubernetes

Who this book is for

This book is ideal for web developers, software engineers, and tech enthusiasts who want to master Blazor for building modern, interactive web applications. Readers should have a basic understanding of web development concepts and familiarity with .NET.

A comprehensive guide to mastering AutoCAD 2024, from basic to intermediate levels, with hands-on exercises and review questions.Key FeaturesComprehensive guide for all levels.Hands-on exercises to solidify learning.Includes review questions similar to Autodesk certification exams.Book DescriptionThis book comprehensively covers AutoCAD 2024 - 2D Drafting, using metric and imperial units. It details drawing and editing tools with companion files for exercises and projects (available for free download). With over 100 exercises, it guides readers from basic commands to complex projects, ensuring no fundamental aspect is overlooked. Starting with AutoCAD basics, the book covers precise drafting, modifying commands, layering, text writing, dimensioning, and plotting. Advanced topics include block tools, table styles, dimension styles, interface customization, parametric constraints, dynamic blocks, external referencing, sheet sets, and CAD standards. This guide is essential for mastering AutoCAD 2024, transitioning users from beginners to proficient drafters with practical skills and comprehensive knowledge. Companion files enhance hands-on practice and mastery of 2D drafting.What you will learnLearn to start AutoCAD and navigate the interface.Understand precise drafting techniques.Master modifying commands.Develop skills in layers and inquiry commands.Explore blocks and hatching.Apply dimensions and plotting techniques.Who this book is forIdeal for novice AutoCAD users and those seeking to become professional power users. No prior experience required, but familiarity with basic computer operations is beneficial. Suitable for students, engineers, architects, and CAD enthusiasts.

Master Excel VBA programming with this concise and practical guide. Learn to automate tasks, enhance productivity, and develop custom functions and macros in Excel 2021.

Key Features

Comprehensive guide to Excel VBA programmingPractical examples and exercisesCovers from basic to advanced techniques

Book Description

This book, part of the successful Pocket Primer series, is designed for those who need to quickly master Excel programming fundamentals. It offers a concise, efficient introduction to VBA, ensuring you only learn what you need to feel comfortable with Excel VBA. The concepts learned in this book also apply to Access programming. The nine chapters progressively introduce you to programming in Microsoft Excel 2021.Starting with a quick guide to Excel macros and the VBA programming environment, the book moves on to fundamental concepts and writing function procedures. You will learn to add decision-making capabilities and looping statements to your programs, store and manage multiple values using arrays and collections, and utilize built-in tools for testing and debugging your code.By the end of the course, you will have a solid foundation in Excel VBA, enabling you to automate tasks and enhance your productivity. This structured approach makes the book an essential resource for mastering Excel VBA efficiently and effectively.

What you will learn

Record and edit macros in ExcelNavigate and utilize the VBA environmentWrite and debug VBA codeUse arrays and collectionsImplement looping and conditional statementsTest and optimize VBA programs

Who this book is for

This book is ideal for Excel users who want to automate tasks, enhance productivity, and develop custom functions. Basic knowledge of Excel is recommended. No prior programming experience is necessary.

A comprehensive guide for IoT engineers, this book integrates data science, machine learning, and systems analytics to provide a robust understanding of modern techniques.

Key Features

Comprehensive integration of systems theory and machine learningFocus on practical applications like digital twinsLogical progression from basics to advanced techniques

Book Description

This book introduces data science to professionals in engineering, physics, mathematics, and related fields. It serves as a workbook with MATLAB code, linking subject knowledge to data science, machine learning, and analytics, with applications in IoT. Part One integrates machine learning, systems theory, linear algebra, digital signal processing, and probability theory. Part Two develops a nonlinear, time-varying machine learning solution for modeling real-life business problems.Understanding data science is crucial for modern applications, particularly in IoT. This book presents a dynamic machine learning solution to handle these complexities. Topics include machine learning, systems theory, linear algebra, digital signal processing, probability theory, state-space formulation, Bayesian estimation, Kalman filter, causality, and digital twins.The journey begins with data science and machine learning, covering systems theory and linear algebra. Advanced concepts like the Kalman filter and Bayesian estimation lead to developing a dynamic machine learning model. The book ends with practical applications using digital twins.

What you will learn

Understand data science fundamentalsApply machine learning techniquesUtilize systems theory and linear algebraPerform digital signal processing in machine learningDevelop adaptive machine learning modelsImplement digital twins for causal analysis

Who this book is for

Ideal for IoT engineers and data scientists, this book requires a basic understanding of mathematics and programming. It is designed for professionals looking to deepen their knowledge in systems theory, machine learning, and analytics.

Comprehensive guide to data structures and programming design using C++. Learn with practical examples and detailed explanations.

Key Features

In-depth coverage of data structures in C++Practical examples and exercisesDetailed explanations of algorithms and their efficiency

Book Description

This book introduces the fundamentals of data structures using C++ in a self-teaching format. It covers managing large amounts of information, SEO, and creating Internet/Web indexing services. Practical analogies with real-world applications help explain technical concepts. The book includes end-of-chapter exercises such as programming tasks, theoretical questions, and multiple-choice quizzes.The course starts with an introduction to data structures and the C++ language, progressing through arrays, linked lists, queues, searching and sorting, stacks, trees, multi-way search trees, hashing, files, and graphs. Each chapter builds on the previous one, ensuring a comprehensive understanding of data structures.Understanding these concepts is crucial for managing large databases and optimizing web services. This book guides readers from basic to advanced data structure techniques, blending theoretical knowledge with practical skills. Companion files with source code and data sets enhance the learning experience, making this book an essential resource for mastering data structures with C++.

What you will learn

Understand the fundamentals of data structuresImplement various data structures using C++Analyze algorithm efficiencyDesign efficient algorithmsSolve programming problemsApply data structures to real-world scenarios

Who this book is for

The ideal audience for this book includes computer science students, software developers, and programming enthusiasts who want to master data structures using C++. Readers should have a basic understanding of programming concepts. Familiarity with C++ is recommended but not mandatory, as the book covers the necessary fundamentals.

This is a comprehensive guide on digital signal processing, covering from basics to advanced applications. Ideal for students and professionals.

Key Features

Comprehensive coverage of DSP fundamentalsPractical applications in speech and radarDetailed exercises and numerical problems

Book Description

This book covers the fundamental concepts of digital signal processing (DSP), introducing discrete-time signals, the z-transform, frequency analysis, discrete and fast Fourier transforms, digital filters, FIR, and statistical DSP. With applications ranging from engineering to telecommunications and medical imaging, this text focuses on representing signals with mathematical models and processing them using discrete-time systems.Understanding DSP is crucial for professionals in various fields as it allows for effective signal representation and manipulation. The book starts with an introduction to DSP and a review of discrete-time signals and systems, followed by a detailed exploration of the z-transform and frequency analysis using DTFT. It further delves into discrete Fourier transforms, fast Fourier transform algorithms, and the implementation of discrete-time systems.The journey continues with in-depth discussions on digital filters, including the design and analysis of infinite impulse response (IIR) and finite impulse response (FIR) filters. The book also covers statistical digital signal processing, multirate DSP, and applications in speech and radar. Through a variety of exercises and a comprehensive glossary, readers will gain a solid understanding of DSP fundamentals and applications.

What you will learn

Understand the basics of DSPExplore discrete-time signalsLearn about z-TransformsMaster Fourier TransformsDesign digital filtersApply DSP in speech and radar

Who this book is for

Ideal for students, engineers, and professionals in electronics and communications. Basic knowledge of signal processing is recommended. Prior understanding of calculus and linear algebra is beneficial.

Learn Python 3, machine learning, and data visualization with ChatGPT/GPT-4. Enhance your data science skills with practical tutorials and real-world applications.

Key Features

Comprehensive coverage of Python librariesPractical applications with real dataCompanion files with source code and datasets available

Book Description

This book bridges the gap between theoretical knowledge and practical application in Python programming, machine learning, and using ChatGPT-4 in data science. It starts with an introduction to Pandas for data manipulation and analysis. The book then explores various machine learning classifiers, from kNN to SVMs. Later chapters cover GPT-4''s capabilities, enhancing linear regression analysis, and using ChatGPT in data visualization, including AI apps, GANs, and DALL-E.The journey begins with mastering Pandas and machine learning fundamentals. It progresses to applying GPT-4 in linear regression and machine learning classifiers. The final chapters focus on using ChatGPT for data visualization, making complex results accessible and understandable.Understanding these concepts is crucial for modern data scientists. This book transitions readers from basic Python programming to advanced applications of ChatGPT-4 in data science. Companion files with source code, datasets, and figures enhance learning, making this an essential resource for mastering Python, machine learning, and AI-driven data visualization.

What you will learn

Master data manipulation with PandasImplement various Machine Learning algorithmsUtilize GPT-4 for regression analysisCreate advanced visualizationsApply ChatGPT in data scienceUnderstand clustering techniques

Who this book is for

This book is ideal for students, data scientists, and AI researchers who want to deepen their understanding and enhance their skills in Python programming, data visualization, and machine learning. Basic knowledge of Python and data science is recommended.

Master advanced computer security and encryption techniques with this comprehensive guide covering cryptography, IPSEC, VPNs, and emerging technologies.Key FeaturesComprehensive coverage of security concepts and encryption techniquesIn-depth exploration of IPSEC and VPN configurationsPractical insights into securing emerging technologiesBook DescriptionThis book addresses the rapid growth of cybercrime by focusing on cryptography and system security. It emphasizes rigorous security models and practices in network and system design. The first part introduces system security concepts, object models, and inter-object communications, providing a foundation in cryptography for beginners and advanced readers alike. The course starts with basic security concepts, moving to public key cryptography, SSL, and transaction security on the web. It covers IP security, firewalls, public key certificates, and security at the IP layer. Readers will also learn about remote access with Internet Protocol security and virtual private networks. The final chapters address the security of emerging technologies like Big Data Analytics, cloud computing, IoT, Smart Grid, SCADA, control systems, and Wireless Sensor Networks. Understanding these concepts is crucial for protecting against cyber threats. This book transitions readers from basic knowledge to advanced security practices, blending theoretical insights with practical applications. It is an invaluable resource for mastering cryptography and system security in today's digital age.What you will learnUnderstand fundamental security conceptsImplement public key cryptographySecure web transactionsConfigure IPSEC and firewallsManage public key certificatesProtect emerging technologiesWho this book is forIdeal for IT professionals, security analysts, and network administrators, this book assumes a basic understanding of computer networks and security principles. Readers should be familiar with fundamental cryptographic concepts and network security basics.

Delve into the essential aspects of market research and analysis, exploring both qualitative and quantitative techniques, and learn to make informed business decisions. Perfect for business professionals and graduate students.

Key Features

General understanding of market research and its applications.Comprehensive coverage of both quantitative and qualitative primary research methods.Advanced data analysis techniques including descriptive statistics, hypothesis testing, and inferential statistics.

Book Description

This book offers an in-depth exploration of market research and analysis, guiding readers through the entire process from defining research objectives to communicating results. Begin by understanding the purpose and ethics of market research, laying a strong groundwork for your studies. Progress to defining precise research objectives and exploring secondary research methods to gather existing information.Next, engage with primary research methods, focusing on both quantitative and qualitative approaches. Learn how to develop and distribute surveys, choose the right sampling techniques, and utilize tools for data mining and web scraping. Gain insights into focus groups and observation studies, understanding how these qualitative methods can provide depth to your research.Finally, master the art of data analysis and result communication. Explore descriptive statistics, hypothesis testing, and inferential statistics to make sense of your data. Learn to effectively present your findings to stakeholders, ensuring your research translates into actionable insights. By the end of the course, you will be well-equipped to conduct thorough market research and communicate your results effectively.

What you will learn

Understand the six steps of market researchConduct qualitative researchConduct quantitative researchAnalyze data effectivelyTest hypothesesCommunicate research findings

Who this book is for

The ideal audience for this book includes business management professionals and graduate students. Readers should have a basic understanding of business concepts and statistical methods. The book is suitable for those looking to deepen their knowledge of market research and enhance their decision-making skills.

Master AI, machine learning, and deep learning with practical insights into RNNs, LSTMs, NLP, and reinforcement learning.Key FeaturesIn-depth coverage of AI, machine learning, and deep learning conceptsPractical examples and hands-on tutorialsIntegration with Keras, TensorFlow, and Pandas for real-world applicationsBook DescriptionThis book introduces AI, then explores machine learning, deep learning, natural language processing (NLP), and reinforcement learning. Readers learn about classifiers like logistic regression, k-NN, decision trees, random forests, and SVMs. It delves into deep learning architectures such as CNNs, RNNs, LSTMs, and autoencoders, with Keras-based code samples supplementing the theory. Starting with a foundational AI overview, the course progresses into machine learning, explaining classifiers and their applications. It continues with deep learning, focusing on architectures like CNNs and RNNs. Advanced topics include LSTMs and autoencoders, essential for modern AI. The book also covers NLP and reinforcement learning, emphasizing their importance. Understanding these concepts is vital for developing advanced AI systems. This book transitions you from beginner to proficient AI practitioner, combining theoretical knowledge and practical skills. Appendices on Keras, TensorFlow 2, and Pandas enrich the learning experience. By the end, readers will understand AI principles and be ready to apply them in real-world scenarios.What you will learnUnderstand AI and its componentsApply machine learning algorithmsImplement deep learning modelsWork with RNNs and LSTMsExplore NLP techniquesUtilize Keras, TensorFlow, and Pandas effectivelyWho this book is forDevelopers, data scientists, and AI enthusiasts looking to deepen their knowledge of AI, machine learning, and deep learning. Basic understanding of programming and statistics is recommended. Familiarity with Python is beneficial.

Unlock the potential of NLP and machine learning with this comprehensive guide. Learn advanced techniques, implement practical applications, and master tools like NumPy, Pandas, and transformer models.

Key Features

Comprehensive guide to NLP and machine learningPractical examples and code samplesCovers from basic to advanced techniques and applications

Book Description

This book introduces developers to basic concepts in NLP and machine learning, providing numerous code samples to support the topics covered. The journey begins with introductory material on NumPy and Pandas, essential for data manipulation. Following this, chapters delve into NLP concepts, algorithms, and toolkits, providing a solid foundation in natural language processing.As you progress, the book covers machine learning fundamentals and classifiers, demonstrating how these techniques are applied in NLP. Practical examples using TF2 and Keras illustrate how to implement various NLP tasks. Advanced topics include the Transformer architecture, BERT-based models, and the GPT family of models, showcasing the latest advancements in the field.The final chapters and appendices offer a comprehensive overview of related topics, including data and statistics, Python3, regular expressions, and data visualization with Matplotlib and Seaborn. Companion files with source code and figures ensure a hands-on learning experience. This book equips you with the knowledge and tools needed to excel in NLP and machine learning.

What you will learn

Master NumPy and Pandas for data manipulationUnderstand NLP concepts and techniquesImplement various NLP algorithmsApply machine learning techniquesUse transformer models like BERT and GPTDevelop practical NLP applications

Who this book is for

This book is ideal for developers and data scientists who want to enhance their skills in NLP and machine learning. Basic knowledge of Python is recommended. Prior experience with data manipulation and machine learning concepts is beneficial.

A comprehensive guide to mastering Autodesk Revit 2024 Architecture, covering both basic and advanced features through practical, step-by-step exercises.Key FeaturesComprehensive coverage of Revit 2024 from basics to advanced featuresPractical exercises and examples to reinforce learningStep-by-step instructions for creating and managing building modelsBook DescriptionThis book covers all major techniques in Revit 2024 Architecture using both metric and imperial units. It details the myriad drawing and editing tools and includes over 50 "e;mini-workshops"e; that guide users from concept to plotting. By solving these workshops, readers will master Revit Architecture, covering all basic commands and functions. Companion files with templates and models are available for practical application. The course begins with an introduction to Revit 2024, followed by detailed chapters on drawing, modifying, project preparation, and wall construction. Subsequent chapters cover doors, windows, curtain walls, floors, roofs, components, and ceilings. Users will also learn about creating stairs, ramps, railings, views, annotations, legends, and visualization. Further, the book delves into schedules, project phasing, design options, topography, rooms, tagging, detailing, groups, file import/export, mass creation, and customizing elements. It concludes with chapters on creating and customizing families, and managing worksets and shared views, ensuring comprehensive knowledge and skills in Revit 2024 Architecture.What you will learnUnderstand the difference between CAD and BIMNavigate and use Revit interfaceDraw and modify building componentsPrepare and manage projectsCreate and manipulate walls, doors, windows, and other elementsVisualize and document your designWho this book is forThis book is ideal for architecture students, educators, and professionals who want to master Autodesk Revit 2024. Readers should have a basic understanding of architectural design principles. No prior experience with Revit is necessary, but familiarity with CAD tools is beneficial.