Products related to Detection:
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Data Analytics & Visualization All-in-One For Dummies
Install data analytics into your brain with this comprehensive introduction Data Analytics & Visualization All-in-One For Dummies collects the essential information on mining, organizing, and communicating data, all in one place.Clocking in at around 850 pages, this tome of a reference delivers eight books in one, so you can build a solid foundation of knowledge in data wrangling.Data analytics professionals are highly sought after these days, and this book will put you on the path to becoming one.You’ll learn all about sources of data like data lakes, and you’ll discover how to extract data using tools like Microsoft Power BI, organize the data in Microsoft Excel, and visually present the data in a way that makes sense using a Tableau.You’ll even get an intro to the Python, R, and SQL coding needed to take your data skills to a new level.With this Dummies guide, you’ll be well on your way to becoming a priceless data jockey. Mine data from data sourcesOrganize and analyze data Use data to tell a story with TableauExpand your know-how with Python and R New and novice data analysts will love this All-in-One reference on how to make sense of data.Get ready to watch as your career in data takes off.
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Spatial Analysis with R : Statistics, Visualization, and Computational Methods
In the five years since the publication of the first edition of Spatial Analysis: Statistics, Visualization, and Computational Methods, many new developments have taken shape regarding the implementation of new tools and methods for spatial analysis with R.The use and growth of artificial intelligence, machine learning and deep learning algorithms with a spatial perspective, and the interdisciplinary use of spatial analysis are all covered in this second edition along with traditional statistical methods and algorithms to provide a concept-based problem-solving learning approach to mastering practical spatial analysis.Spatial Analysis with R: Statistics, Visualization, and Computational Methods, Second Edition provides a balance between concepts and practicums of spatial statistics with a comprehensive coverage of the most important approaches to understand spatial data, analyze spatial relationships and patterns, and predict spatial processes.New in the Second Edition: Includes new practical exercises and worked-out examples using R Presents a wide range of hands-on spatial analysis worktables and lab exercises All chapters are revised and include new illustrations of different concepts using data from environmental and social sciences Expanded material on spatiotemporal methods, visual analytics methods, data science, and computational methods Explains big data, data management, and data miningThis second edition of an established textbook, with new datasets, insights, excellent illustrations, and numerous examples with R, is perfect for senior undergraduate and first-year graduate students in geography and the geosciences.
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Spatial Analysis with R : Statistics, Visualization, and Computational Methods
In the five years since the publication of the first edition of Spatial Analysis: Statistics, Visualization, and Computational Methods, many new developments have taken shape regarding the implementation of new tools and methods for spatial analysis with R.The use and growth of artificial intelligence, machine learning and deep learning algorithms with a spatial perspective, and the interdisciplinary use of spatial analysis are all covered in this second edition along with traditional statistical methods and algorithms to provide a concept-based problem-solving learning approach to mastering practical spatial analysis.Spatial Analysis with R: Statistics, Visualization, and Computational Methods, Second Edition provides a balance between concepts and practicums of spatial statistics with a comprehensive coverage of the most important approaches to understand spatial data, analyze spatial relationships and patterns, and predict spatial processes.New in the Second Edition: Includes new practical exercises and worked-out examples using R Presents a wide range of hands-on spatial analysis worktables and lab exercises All chapters are revised and include new illustrations of different concepts using data from environmental and social sciences Expanded material on spatiotemporal methods, visual analytics methods, data science, and computational methods Explains big data, data management, and data miningThis second edition of an established textbook, with new datasets, insights, excellent illustrations, and numerous examples with R, is perfect for senior undergraduate and first-year graduate students in geography and the geosciences.
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Virus Detection
Viruses do not behave as other microbes; their life cycles require infecting healthy cells, commandeering their cellular apparatus, replicating and then killing the host cell.Methods for virus detection and identification have been developed only in the past few decades.These recently developed methods include molecular, physical, and proteomic techniques.All these approaches (Electron Microscopy, Molecular, Direct Counting, and Mass Spectrometry Proteomics) to detection and identification are reviewed in this succinct volume.It is written in approachable language with enough detail for trained professionals to follow and want to recommend to others. Key Features Covers common detection methods Reviews the history of detection from antiquity to the present Documents the strengths and weaknesses of various detection methods Describes how to detect newly discovered viruses Recommends specific applications for clinical, hospital, environmental, and public health uses
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What is the detection limit or limit of detection?
The detection limit, also known as the limit of detection, is the lowest concentration of a substance that can be reliably detected by a particular analytical method. It represents the smallest amount of analyte that can be distinguished from the background noise of the measurement. Detection limits are important in determining the sensitivity and reliability of an analytical technique, as they indicate the smallest quantity of a substance that can be accurately measured. Scientists strive to minimize detection limits in order to improve the accuracy and precision of their measurements.
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What is spatial visualization ability?
Spatial visualization ability refers to the capacity to mentally manipulate and comprehend spatial relationships between objects. Individuals with strong spatial visualization skills can easily visualize and understand how objects relate to each other in space, such as rotating or manipulating shapes in their mind. This ability is crucial in various fields such as engineering, architecture, and mathematics, as it allows individuals to solve complex problems and understand spatial concepts more effectively. Improving spatial visualization ability can enhance problem-solving skills and overall cognitive performance.
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Is spatial visualization important for engineers?
Yes, spatial visualization is important for engineers as it allows them to mentally manipulate and understand complex 3D objects and structures. Engineers often need to design and analyze various components and systems, and spatial visualization skills help them to conceptualize and communicate their ideas effectively. Whether it's designing a new product, creating blueprints for a building, or solving complex problems, spatial visualization is a crucial skill that allows engineers to think critically and innovate in their field.
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What is a halide detection?
Halide detection refers to the process of identifying and measuring the presence of halide ions, such as chloride, bromide, and iodide, in a sample. This can be done using various analytical techniques, such as ion chromatography, colorimetric assays, or electrochemical sensors. Halide detection is important in environmental monitoring, industrial processes, and medical diagnostics, as the presence of halides can indicate contamination, corrosion, or specific health conditions. Accurate and sensitive detection of halides is crucial for ensuring safety and quality in various applications.
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Crime Mapping and Spatial Data Analysis using R
Crime mapping and analysis sit at the intersection of geocomputation, data visualisation and cartography, spatial statistics, environmental criminology, and crime analysis.This book brings together relevant knowledge from these fields into a practical, hands-on guide, providing a useful introduction and reference material for topics in crime mapping, the geography of crime, environmental criminology, and crime analysis.It can be used by students, practitioners, and academics alike, whether to develop a university course, to support further training and development, or to hone skills in self-teaching R and crime mapping and spatial data analysis.It is not an advanced statistics textbook, but rather an applied guide and later useful reference books, intended to be read and for readers to practice the learnings from each chapter in sequence.In the first part of this volume we introduce key concepts for geographic analysis and representation and provide the reader with the foundations needed to visualise spatial crime data.We then introduce a series of tools to study spatial homogeneity and dependence.A key focus in this section is how to visualise and detect local clusters of crime and repeat victimisation.The final chapters introduce the use of basic spatial models, which account for the distribution of crime across space.In terms of spatial data analysis the focus of the book is on spatial point pattern analysis and lattice or area data analysis.
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Spatial Epidemiological Approaches in Disease Mapping and Analysis
Containing method descriptions and step-by-step procedures, the Spatial Epidemiological Approaches in Disease Mapping and Analysis equips readers with skills to prepare health-related data in the proper format, process these data using relevant functions and software, and display the results as mapped or statistical summaries.Describing the wide range of available methods and key GIS concepts for spatial epidemiology, this book illustrates the utilities of the software using real-world data.Additional topics include geographic data models, address matching, geostatistical analysis, universal kriging, point pattern analysis, kernel density, spatio-temporal display, and disease surveillance.
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Unstructured Data Analytics : How to Improve Customer Acquisition, Customer Retention, and Fraud Detection and Prevention
Turn unstructured data into valuable business insight Unstructured Data Analytics provides an accessible, non-technical introduction to the analysis of unstructured data.Written by global experts in the analytics space, this book presents unstructured data analysis (UDA) concepts in a practical way, highlighting the broad scope of applications across industries, companies, and business functions.The discussion covers key aspects of UDA implementation, beginning with an explanation of the data and the information it provides, then moving into a holistic framework for implementation.Case studies show how real-world companies are leveraging UDA in security and customer management, and provide clear examples of both traditional business applications and newer, more innovative practices. Roughly 80 percent of today's data is unstructured in the form of emails, chats, social media, audio, and video.These data assets contain a wealth of valuable information that can be used to great advantage, but accessing that data in a meaningful way remains a challenge for many companies.This book provides the baseline knowledge and the practical understanding companies need to put this data to work. Supported by research with several industry leaders and packed with frontline stories from leading organizations such as Google, Amazon, Spotify, LinkedIn, Pfizer Manulife, AXA, Monster Worldwide, Under Armour, the Houston Rockets, DELL, IBM, and SAS Institute, this book provide a framework for building and implementing a successful UDA center of excellence. You will learn: How to increase Customer Acquisition and Customer Retention with UDAThe Power of UDA for Fraud Detection and PreventionThe Power of UDA in Human Capital Management & Human ResourceThe Power of UDA in Health Care and Medical ResearchThe Power of UDA in National SecurityThe Power of UDA in Legal ServicesThe Power of UDA for product developmentThe Power of UDA in SportsThe future of UDA From small businesses to large multinational organizations, unstructured data provides the opportunity to gain consumer information straight from the source.Data is only as valuable as it is useful, and a robust, effective UDA strategy is the first step toward gaining the full advantage.Unstructured Data Analytics lays this space open for examination, and provides a solid framework for beginning meaningful analysis.
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MultiVersus: Collision Detection
The hit video game has jumped from your screen into the DC Universe! When the heroes of the DCU are troubled by strange dreams and mysterious figures, they decide to investigate.Why is Batman dreaming of the rabbit and why does Wonder Woman have something called the star child on her brain?Why is Superman thinking about the witch ? What does any of this mean? Well, things might start to become a bit more clear when they come face-to-face with the one and only Bugs Bunny!There are big things brewing in the multiverse and no world is safe! Collected MultiVersus: Collision Detected #1-6.
Price: 16.99 £ | Shipping*: 3.99 £
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What is Apple's fall detection?
Apple's fall detection is a feature available on certain Apple Watch models that can automatically detect if the wearer has taken a hard fall. When a fall is detected, the watch will tap the wearer on the wrist, sound an alarm, and display an alert. If the wearer does not respond within a minute, the watch will automatically call emergency services and send a message to the wearer's emergency contacts with their location. This feature is designed to provide an added layer of safety and peace of mind for Apple Watch users, particularly for those who may be at risk of falling.
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What are chemical detection reactions?
Chemical detection reactions are specific chemical reactions that are used to detect the presence of a particular substance or compound. These reactions often produce a visible color change, gas release, or precipitation, which can be easily observed and used to identify the presence of the target compound. Chemical detection reactions are commonly used in analytical chemistry, environmental monitoring, and forensic science to identify and quantify the presence of various substances in a sample. These reactions are highly specific and sensitive, allowing for accurate detection and analysis of target compounds.
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Can one improve their spatial visualization skills?
Yes, it is possible to improve spatial visualization skills through practice and training. Engaging in activities such as puzzles, building models, and playing spatial reasoning games can help develop these skills. Additionally, practicing mental rotation exercises and regularly challenging oneself with spatial tasks can also contribute to improvement. With consistent effort and dedication, individuals can enhance their spatial visualization abilities over time.
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What are problems with spatial visualization skills?
Some problems with spatial visualization skills include difficulty in understanding and interpreting maps, graphs, and diagrams. Individuals with poor spatial visualization skills may struggle with tasks such as navigating through unfamiliar environments, understanding 3D objects, and mentally rotating objects. This can impact their performance in subjects such as math, science, and engineering, as well as in everyday activities such as driving and assembling furniture. Additionally, poor spatial visualization skills can lead to frustration and decreased confidence in one's abilities.
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