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.

Data Analytics. Master the Art of Data Analytics with Essential Tools and Techniques

Mercury Learning and Information, Christopher Greco

Data analytics is becoming increasingly important in our daily lives. This book offers a comprehensive view of data analytics skills, starting with a primer on statistics and progressing to the application of these methods. The text includes various formulas and algorithms used in data analytics, which can be applied in any software to achieve desired results. Through numerous demonstrations, it provides clear instruction on how to incorporate data analytics into critical thinking.The book covers a range of methods and techniques, supplemented with case studies specific to project managers, systems engineers, and cybersecurity professionals. Each profession can practice data analytics relevant to their fields. The main objective is to refresh statistical knowledge necessary for building data analytics models and to foster analytical thinking essential across these professions.From introducing statistics and data to reviewing central tendency measures and probability, the book moves to more complex topics like effect size, analysis methods, and data presentation. By the end of the course, readers will be well-versed in data analytics, ready to apply these skills effectively in their respective fields, enhancing decision-making and analytical thinking.

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 2025 3D Modeling. Master essential 3D modeling techniques with AutoCAD 2025

Mercury Learning and Information, Munir Hamad

Master the art of 3D modeling with this comprehensive book tailored for AutoCAD 2025. Designed for beginners and experienced users alike, this book begins with an introduction to the AutoCAD 3D environment, providing clear and concise instructions for navigating its interface and essential tools. By building a strong foundation, it sets the stage for more advanced techniques.As the chapters progress, readers are introduced to creating and editing solids, meshes, and surfaces, exploring AutoCAD’s powerful commands and features. Learn how to apply realistic materials, incorporate lighting, and generate stunning 3D renderings to bring your designs to life. The guide also delves into converting and sectioning tools, enabling you to create detailed and precise outputs for professional use.By the end of this book, readers will have acquired a deep understanding of AutoCAD’s 3D capabilities, empowering them to tackle complex design challenges with confidence. Whether you are an architect, engineer, or CAD enthusiast, this guide will equip you with the skills to enhance productivity and deliver outstanding results.

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.

Network Security and Cryptography. A Comprehensive Guide to Network Protection and Encryption Techniques

Mercury Learning and Information, Sarhan M. Musa

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.

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.

Data Science Tools. Comprehensive Guide to Mastering Fundamental Data Science and Statistics Techniques

Mercury Learning and Information, Christopher Greco

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.