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Podcasts
Mercury Learning and Information, P. G. Madhavan
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.
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.
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.
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++.
Mercury Learning and Information, D. Malhotra, N. Malhotra
This book introduces the fundamentals of data structures using Java in a self-teaching format. It covers managing large databases, effective SEO, and creating web indexing services. Real-world analogies help explain technical concepts. Each chapter includes programming tasks, theoretical questions, and multiple-choice quizzes.The course begins with an introduction to data structures and Java, moving 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 thorough understanding of data structures.Understanding these concepts is crucial for managing information and optimizing web services. This book guides readers from basic to advanced techniques, blending theory with practical skills. It is an essential resource for mastering data structures with Java, enhanced by end-of-chapter exercises and real-world examples.
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.
Data Visualization for Business Decisions. Transforming Data into Actionable Insights
Mercury Learning and Information, Andres Fortino
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.
Mercury Learning and Information, Oswald Campesato
This book is designed for aspiring data scientists and those involved in data cleaning. It covers features of NumPy and Pandas, along with creating databases and tables in MySQL. It also addresses various data wrangling tasks using Python scripts and awk-based shell scripts. Companion files with code are available from the publisher.Understanding data cleaning and manipulation is vital for data scientists. This book provides a comprehensive introduction to essential tools and techniques. From Python basics to advanced data wrangling, it equips readers with the skills needed to manage and clean data effectively.The journey begins with an introduction to Python and progresses through working with data, Pandas, and SQL. It also covers Java, JSON, XML, and specific data cleaning tasks. The book culminates with detailed data wrangling techniques, ensuring readers gain practical, hands-on experience in data management.
Dealing With Data Pocket Primer. A Comprehensive Guide to Data Handling Techniques
Mercury Learning and Information, Oswald Campesato
This book introduces the basic concepts of managing data using various computer languages and applications. It is designed as a fast-paced introduction to key features of data management, including statistical concepts, data-related techniques, Pandas, RDBMS, SQL, NLP topics, Matplotlib, and data visualization. The companion files with source code and color figures enhance the learning experience.Understanding these concepts is crucial for anyone looking to manage data effectively. The book covers the fundamentals of probability and statistics, working with data using Pandas, managing databases with SQL and MySQL, and cleaning data using NLP techniques. It also delves into data visualization, providing practical insights and numerous code samples.The journey begins with an introduction to probability and statistics, moving on to working with data and Pandas. It then covers RDBMS and SQL, focusing on practical SQL and MySQL usage. The book concludes with NLP, data cleaning, and visualization techniques, equipping readers with a comprehensive understanding of data management.
Mercury Learning and Information, R. Anand
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.
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.
Embedded Vision. Mastering Advanced Techniques for Real-Time Image Processing and Analysis
Mercury Learning and Information, S. R. Vijayalakshmi, S. Muruganand
Embedded vision integrates computer vision into machines using algorithms to interpret images or videos. This book serves as an introductory guide for designing vision-enabled embedded products, with applications in AI, machine learning, industrial, medical, automotive, and more. It covers hardware architecture, software algorithms, applications, and advancements in cameras, processors, and sensors.The course begins with an overview of embedded vision, followed by industrial and medical vision applications. It then delves into video analytics, digital image processing, and camera-image sensors. Subsequent chapters cover embedded vision processors, computer vision, and AI integration. The final chapter presents real-time vision-based examples.Understanding these concepts is vital for developing advanced vision-enabled machines. This book takes readers from the basics to advanced topics, blending theoretical knowledge with practical applications. It is an essential resource for mastering embedded vision technology across various industries.
Empirical Cloud Security. A Guide To Practical Intelligence to Evaluate Risks and Attacks
Mercury Learning and Information, Aditya K. Sood
This book, updated to include the latest research and developments in cloud security, is essential for security professionals, DevOps engineers, penetration testers, cloud security engineers, and cloud software developers. It offers practical approaches to securing cloud infrastructure and applications against threats, attacks, and data breaches. The content is refined for better accessibility and engagement, providing a comprehensive guide to cloud security.The course starts with fundamental cloud security concepts and progresses to hands-on assessment techniques based on real-world case studies. It covers cloud architecture, IAM for authentication and authorization, network security, database and storage security, cryptography controls, secure code review, and monitoring and logging. The practical strategies for assessing security and privacy are crucial for building a robust cloud infrastructure.The journey concludes with advanced topics such as privacy in the cloud, identifying security flaws and attacks, and understanding the impact of malicious code. New case studies reveal how threat actors exploit cloud environments, offering preventative measures to enhance cloud security. This structured approach ensures a thorough understanding and practical application of cloud security principles.
Mercury Learning and Information, William Kimmerly
This book guides organizations in effectively responding to the metaverse, a rapidly converging collection of advanced technologies, methods, and models. The metaverse is poised to be as disruptive as the personal computer, Internet, and smartphone, impacting personal, social, professional, and business lives. The book covers essential metaverse technologies and concepts, helping organizational leaders plan their transformation strategies.The journey begins with an introduction and key definitions, followed by the evolution of IT governance and responses to disruptive technologies. It delves into AI, machine learning, blockchain, platforms, algorithms, edge computing, quantum computing, and immersive technologies like VR, AR, MR, and XR. Further chapters explore holographic technologies, deep tech, and other metaverse-related technologies, along with organizational structures and governance frameworks for the metaverse era.Understanding these concepts is crucial for navigating the metaverse transformation. The book concludes with a detailed hypothetical case study, illustrating how such a transformation can be achieved. This resource helps executives and professionals chart an effective course to the metaverse, blending theoretical insights with practical applications.
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.
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.