Data Structures and Program Design Using C++. A Self-Teaching Introduction to Data Structures and C++

Mercury Learning and Information, D. Malhotra, N. Malhotra

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++.

The Creation of a Conscious Machine. The AI Quest: Building Awareness with Advanced Artificial Intelligence Technologies

Mercury Learning and Information, Jean E. Tardy

This book delves into Generative AI and the potential for AI to achieve consciousness. It covers historical and modern perspectives on AI, from ancient myths to the Turing Test and current advancements. The book explores the theoretical and practical aspects of creating a conscious AI, including specifications for synthetic consciousness and integrating AI with human cognition. It questions whether generative AI can meet traditional criteria of consciousness.The journey begins with understanding consciousness, tracing AI's origins, and clarifying human cognition through AI. It examines early AI failures, fears of success, and the engineering of consciousness. The book also explores archaic AI representations, the intelligence of automatons, and the relevance of the Turing Test, concluding with strategies for achieving synthetic consciousness.These concepts are crucial for advancing AI towards synthetic consciousness. This book transitions readers from historical perspectives to modern AI challenges, blending theory with practical insights. It is an essential resource for understanding the future of AI and its potential to achieve consciousness.

Data Structures and Program Design Using Python. A Self-Teaching Introduction to Data Structures and Python

Mercury Learning and Information, D. Malhotra, N. Malhotra

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.

Artificial Intelligence Basics. A Self-Teaching Introduction

Mercury Learning and Information, N. Gupta, R. Mangla

This 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.

Data Science Fundamentals Pocket Primer. An Essential Guide to Data Science Concepts and Techniques

Mercury Learning and Information, Oswald Campesato

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.

Microsoft Excel 2021 Programming Pocket Primer. A Comprehensive Guide to Mastering Excel VBA

Mercury Learning and Information, Julitta Korol

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.

Python 3 for Machine Learning. Harness the Power of Python for Advanced Machine Learning Projects

Mercury Learning and Information, Oswald Campesato

This book introduces basic Python 3 programming concepts related to machine learning. The first four chapters provide a fast-paced introduction to Python 3, NumPy, and Pandas. The fifth chapter covers fundamental machine learning concepts. The sixth chapter dives into machine learning classifiers, such as logistic regression, k-NN, decision trees, random forests, and SVMs. The final chapter includes material on natural language processing (NLP) and reinforcement learning (RL). Keras-based code samples supplement the theoretical discussion.The course begins with Python basics, including conditional logic, loops, functions, and collections. It then explores data manipulation with NumPy and Pandas. The journey continues with an introduction to machine learning, focusing on essential concepts and classifiers. Advanced topics like NLP and RL are covered, ensuring a comprehensive understanding of machine learning.These concepts are crucial for developing machine learning applications. This book transitions readers from basic Python programming to advanced machine learning techniques, blending theory with practical skills. Appendices for regular expressions, Keras, and TensorFlow 2, along with companion files, enhance learning, making this an essential resource for mastering Python and machine learning.

AutoCAD 2024 Beginning and Intermediate. Mastering 2D Drafting Techniques for All Levels

Mercury Learning and Information, Munir Hamad

This 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.

Computer Graphics Programming in OpenGL With C++ (Edition 3). Mastering 3D Graphics and Animation Techniques

Mercury Learning and Information, V. Scott Gordon, John L. Clevenger

This 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.

Mathematics for Business. Explore Essential Mathematical Concepts and Techniques for Decision Making

Mercury Learning and Information, Gary Bronson, Richard Bronson, Maureen Kieff

This course provides a comprehensive understanding of quantitative methods essential for economic forecasting, resource allocation, portfolio analysis, inventory management, data-mining, and addressing social and climate challenges. Starting with foundational topics like finite mathematics and the mathematics of finance, it progresses to differential calculus, optimization, and curve fitting. These concepts are vital for solving contemporary business problems.Learners will explore algebra, finite math, finance mathematics, calculus, optimization techniques, and curve fitting, applying these methods to realistic business scenarios. Topics include cash flow, amortization, interest, loans, annuities, revenue/cost models, break-even analysis, inventory control, and econometrics. Each section includes extensive examples and exercises, reinforced by key terms and concepts, making the material accessible and practical.The course begins with basic mathematical concepts and advances through increasingly complex topics. By the end, learners will have the tools to tackle various business problems using quantitative methods, making this course invaluable for anyone in the business field. This structured approach ensures both theoretical knowledge and practical application, preparing learners for real-world challenges.

Natural Language Processing Fundamentals for Developers. A Practical Guide to Building NLP Applications

Mercury Learning and Information, Oswald Campesato

This book is for developers seeking an overview of basic concepts in Natural Language Processing (NLP). It caters to those with varied technical backgrounds, offering numerous code samples and listings to illustrate the wide range of topics covered. The journey begins with managing data relevant to NLP, followed by two chapters on fundamental NLP concepts. This foundation is reinforced with Python code samples that bring these concepts to life.The book then delves into practical NLP applications, such as sentiment analysis, recommender systems, COVID-19 analysis, spam detection, and chatbots. These examples provide real-world context and demonstrate how NLP techniques can be applied to solve common problems. The final chapter introduces advanced topics, including the Transformer architecture, BERT-based models, and the GPT family, highlighting the latest state-of-the-art developments in the field.Appendices offer additional resources, including Python code samples on regular expressions and probability/statistical concepts, ensuring a well-rounded understanding. Companion files with source code and figures enhance the learning experience, making this book a comprehensive guide for mastering NLP techniques and applications.

Discrete Mathematics With Cryptographic Applications. A Self-Teaching Guide to Unlocking the Power of Advanced Concepts and Computational Techniques

Mercury Learning and Information, Alexander I. Kheyfits

This book offers a comprehensive guide to discrete mathematics and its applications to cryptography. It is designed for students and professionals in fields such as discrete mathematics and finite mathematics, with all necessary prerequisites clearly explained and illustrated. The text introduces key concepts in number theory, coding theory, and information theory, which are essential for understanding cryptography.Understanding discrete mathematics is crucial for anyone working in cryptography and related fields. The book begins with a survey of elementary functions and moves on to propositional algebra, set theory, and algebraic structures like groups, rings, and fields. It covers binary relations, combinatorics, and elements of number theory, which are fundamental to cryptographic methods.Readers will explore topics such as Boolean functions, hashing functions, cryptographic maps, combinatorial circuits, and graph theory. The book also delves into advanced areas like finite automata, game theory, and Turing machines. Through numerous examples, problems, and solutions, readers will gain a solid foundation in discrete mathematics and its cryptographic applications.

Data Literacy With Python. A Comprehensive Guide to Understanding and Analyzing Data with Python

Mercury Learning and Information, Oswald Campesato

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.

Bash for Data Scientists. A Comprehensive Guide to Shell Scripting for Data Science Tasks

Mercury Learning and Information, Oswald Campesato

This book introduces powerful command line utilities for creating efficient shell scripts to process datasets. Using the bash shell, the examples and scripts focus on small datasets to help readers understand the features of grep, sed, and awk. Companion files with code are available for download from the publisher.The course starts with an introduction to the basics, covering files and directories, and useful commands. It then progresses to conditional logic and loops, providing a solid foundation for processing datasets. Detailed chapters on using grep, sed, and awk illustrate their capabilities in handling and cleaning various types of datasets effectively.Advanced topics include processing datasets with Pandas, exploring NoSQL, SQLite, and Python. The book equips data scientists, analysts, and anyone seeking shell-based solutions with practical skills. By the end, users will be adept at creating robust scripts for dataset processing, combining command line utilities for optimal results.

Tensor Analysis for Engineers. Mastering Coordinate Systems, Transformations and Applications using Mathematics

Mercury Learning and Information, Mehrzad Tabatabaian

This book is a comprehensive guide to tensor analysis for engineers and applied scientists, focusing on practical problem-solving in Euclidean space. It covers Cartesian coordinate systems and curvilinear coordinates like cylindrical and spherical, with examples and calculations. Expanded content includes rigid body rotation, Cartesian tensors, Euler angles, and quaternion methods.The course begins with coordinate systems, moving through curvilinear systems, basis vectors, and scale factors. It covers contravariant and physical components, tensor transformations, and mixed and metric tensors. Advanced topics include gradient operators, derivative forms, Cartesian tensor transformations, and coordinate-independent equations. The book features relations for selected coordinate systems, rigid body rotation methods, and numerous worked-out examples and exercises.Mastering tensor analysis is crucial for complex engineering and science problems. This book transitions from basic concepts to advanced applications, blending theory with practical examples. Clear explanations, figures, and exercises enhance learning, making this an essential resource for tensor analysis in Euclidean space.

Artificial Intelligence, Machine Learning, and Deep Learning. A Practical Guide to Advanced AI Techniques

Mercury Learning and Information, Oswald Campesato

This 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.

Finite Element Analysis. An Introductory Guide to FEM Techniques and Applications

Mercury Learning and Information, Sarhan M. Musa

This comprehensive guide explores the versatility and affordability of Finite Element Analysis (FEA) as a powerful tool for solving engineering problems. The book provides a practical introduction to FEA, covering applications in mechanical, civil, electrical engineering, and physics. It presents a balanced blend of theory and applications, catering to both beginners and those seeking to enhance their FEA skills.The journey begins with mathematical preliminaries and an introduction to the Finite Element Method. It progresses through various applications such as axially loaded members, trusses, beams, stress analysis, thermal analysis, fluid flow analysis, dynamic analysis, and engineering electromagnetics analysis. Each chapter includes comparisons of analytical methods, FEA hand calculations, and software-based solutions, helping readers understand the strengths and limitations of each approach.Understanding these concepts is crucial for effective problem-solving in engineering. This book transitions readers from fundamental principles to advanced engineering applications, blending theoretical knowledge with practical skills. Companion files with executable models and animations enhance the learning experience, making this guide an essential resource for mastering FEA techniques.

Programming Fundamentals Using MATLAB. Master the Basics and Beyond of MATLAB Programming

Mercury Learning and Information, Michael Weeks

This book introduces MATLAB syntax and environment, ideal for beginners with no programming background. The first four chapters cover basic programming concepts, computing terminology, MATLAB syntax, control structures, operators, arrays, and matrices. Next, the book explores grouping data, working with files, creating images, building graphical user interfaces, experimenting with sound, and debugging. The final chapters present case studies on using MATLAB with tools like Arduino, Linux, Git, and Mex, essential for basic programming knowledge.Understanding MATLAB is crucial for data analysis and technical computing. This book transitions readers from basics to advanced topics, blending theoretical knowledge with practical applications. Companion files with code and four-color figures enhance learning, making this an essential resource for mastering MATLAB.

3D Printing. The Complete Guide to Mastering 3D Printing Techniques

Mercury Learning and Information, Stephanie Torta, Jonathan Torta

This book offers a comprehensive introduction to the field of 3D printing, covering its applications in industry, education, and the DIY community. It delves into common 3D printers, materials, and software, guiding you through setting up your own printer and performing essential calibration tasks. Through full-color images, you’ll learn about various printing methods, best practices, and how to finish your projects successfully.The book is divided into three parts: the first part provides a history and evolution of 3D printers, highlighting their industrial and personal use. The second part walks you through setting up a 3D printer, from initial hardware calibration to software functionalities and acquiring 3D objects. You’ll also find step-by-step guides for three different projects.The final part helps you choose the right printer, explains common features, and explores post-market modifications. Understanding 3D printing is crucial as it revolutionizes manufacturing and prototyping processes, enabling creativity and innovation in various fields. This book ensures a smooth journey from a novice to a confident 3D printing enthusiast, equipped with practical skills and knowledge. Companion files with videos, printable objects, and additional lessons enhance your learning experience.

Computer Security and Encryption. Advanced Techniques for Securing Digital Information

Mercury Learning and Information, S. R. Chauhan, S. Jangra

This 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.

Excel Basics. Mastering Excel Foundation and Spreadsheets Efficiently through Formulas & Graphs

Mercury Learning and Information, Jeffrey Hsu, Gary Bronson

This book is designed for first-time or beginning Excel users, providing a comprehensive yet accessible introduction to mastering Microsoft Excel 2019 and previous versions. Starting with the basics, it guides readers through the foundational concepts and features of Excel, ensuring a solid understanding of this essential software. Key topics include an overview of Excel, formulas, functions, formatting, conditional features, graphs, charts, pivot tables, and using a spreadsheet as a database.The book is richly illustrated with screenshots, examples, applications, and exercises to reinforce learning. Suitable for professional reference, self-study, or instructor-led courses, it equips readers with the skills to enhance business and personal productivity. The content is structured to build from basic to advanced topics, making it a valuable resource for users at any stage of learning.With additional resources like tutorial videos, PowerPoint slides, sample syllabi, tests, and quizzes, this book ensures a thorough and engaging learning experience. By the end of the course, users will be proficient in Excel, capable of leveraging its full potential to streamline tasks and improve efficiency.

Python 3 Data Visualization Using ChatGPT / GPT-4. Master Python Visualization Techniques with AI Integration

Mercury Learning and Information, Oswald Campesato

This book teaches Python 3 programming and data visualization, exploring cutting-edge techniques with ChatGPT/GPT-4 for generating compelling visuals. It starts with Python essentials, covering basic data types, loops, functions, and advanced constructs like dictionaries and matrices. The journey progresses to NumPy's array operations and data visualization using libraries such as Matplotlib and Seaborn. The book also covers tools like SVG graphics and D3 for dynamic visualizations.The course begins with foundational Python concepts, moves into NumPy and data visualization with Pandas, Matplotlib, and Seaborn. Advanced chapters explore ChatGPT and GPT-4, demonstrating their use in creating data visualizations from datasets like the Titanic. Each chapter builds on the previous one, ensuring a comprehensive understanding of Python and visualization techniques.These concepts are crucial for Python practitioners, data scientists, and anyone in data analytics. This book transitions readers from basic Python programming to advanced data visualization, blending theoretical knowledge with practical skills. Companion files with code, datasets, and figures enhance learning, making this an essential resource for mastering Python and data visualization.

Game Testing. Mastering the Art of Quality Assurance in Game Development

Mercury Learning and Information, Robert Denton Bryant

This updated fourth edition is your comprehensive guide to video game testing. Whether you're a student aspiring to join the industry or a professional honing your skills, this book covers essential aspects of game testing. It explains how testers fit into development and provides practical knowledge of tools, roles, responsibilities, and metrics for game quality.The book guides you through test design and QA methods using real game scenarios and interviews with veteran developers. You'll learn the basics of game testing, writing bug reports, and defect tracking. The chapters cover exploratory testing, gameplay testing, combinatorial testing, and regression testing.Each chapter includes questions and exercises, suitable for classroom or personal study. Companion files with templates and tutorials for creating combinatorial tables and test flow diagrams are included, forming the basis of a robust QA plan. This edition equips you with the skills to succeed in game testing and contribute effectively to any development team.

Excel 2021 / Microsoft 365 Programming By Example. A Comprehensive Guide to Mastering Excel VBA

Mercury Learning and Information, Julitta Korol

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.