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.