Database design and theory

Understand data science concepts and methodologies to manage and deliver top-notch solutions for your organizationKey FeaturesLearn the basics of data science and explore its possibilities and limitationsManage data science projects and assemble teams effectively even in the most challenging situationsUnderstand management principles and approaches for data science projects to streamline the innovation processBook DescriptionData science and machine learning can transform any organization and unlock new opportunities.

The book explores the critical challenge of securing sensitive medical data in the face of rising cyber threats.

Perform supervised and unsupervised machine learning and learn advanced techniques such as training neural networks.

This concise, easy-to-use reference puts one of the most popular frameworks for deep learning research and development at your fingertips.

Understand how machine learning works and get hands-on experience of using R to build algorithms that can solve various real-world problemsKey FeaturesGain a comprehensive overview of different machine learning techniquesExplore various methods for selecting a particular algorithmImplement a machine learning project from problem definition through to the final modelBook DescriptionWith huge amounts of data being generated every moment, businesses need applications that apply complex mathematical calculations to data repeatedly and at speed.

Python is a first-class tool for many researchers, primarily because of its libraries for storing, manipulating, and gaining insight from data.

Given a set of objects and a pairwise similarity measure between them, the goal of correlation clustering is to partition the objects in a set of clusters to maximize the similarity of the objects within the same cluster and minimize the similarity of the objects in different clusters.

Become the master player of data exploration by creating reproducible data processing pipelines, visualizations, and prediction models for your applications.

Although, the basic concept of a fuel cell is quite simple, creating new designs and optimizing their performance takes serious work and a mastery of several technical areas.

Linked Data (LD) is a well-established standard for publishing and managing structured information on the Web, gathering and bridging together knowledge from different scientific and commercial domains.

Why is Google Analytics 4 the most modern data model available for digital marketing analytics?

Learn how to apply TensorFlow to a wide range of deep learning and Machine Learning problems with this practical guide on training CNNs for image classification, image recognition, object detection and many computer vision challenges.

How can you make sense of the complex IoT landscape?

Pulling aside the curtain of 'Big Data' buzz, this book introduces C-suite and other non-technical senior leaders to the essentials of obtaining and maintaining accurate, reliable data, especially for decision-making purposes.

A comprehensive guide to mastering the most advanced Hadoop 3 conceptsKey FeaturesGet to grips with the newly introduced features and capabilities of Hadoop 3Crunch and process data using MapReduce, YARN, and a host of tools within the Hadoop ecosystemSharpen your Hadoop skills with real-world case studies and codeBook DescriptionApache Hadoop is one of the most popular big data solutions for distributed storage and for processing large chunks of data.

Reinforce your understanding of data science and data analysis from a statistical perspective to extract meaningful insights from your data using Python programmingKey FeaturesWork your way through the entire data analysis pipeline with statistics concerns in mind to make reasonable decisionsUnderstand how various data science algorithms functionBuild a solid foundation in statistics for data science and machine learning using Python-based examplesBook DescriptionStatistics remain the backbone of modern analysis tasks, helping you to interpret the results produced by data science pipelines.

This richly illustrated book examines the full potential of Digital Twins (DTs) as a means of creating more sustainable urban habitats.

This book aims to provide readers with a comprehensive guide to the fundamentals of big data analytics and its applications in various industries and smart societies.

Presents a state-of-the-art review of model error concepts, their characterization and compensation in estimation and control problems, with particular emphasis on error propagation, model order selection, performance guarantees, sensitivity and adaptive methods.

Nowadays, finance, mathematics, and programming are intrinsically linked.

The world's businesses ingest a combined 2.

Cultivating Professional Identity in Design is a nuanced, comprehensive companion for designers across disciplines honing their identities, self-perception, personal strengths, and essential attributes.

Machine learning has redefined the way we work with data and is increasingly becoming an indispensable part of everyday life.

Big data involves the use of sophisticated analytics to make decisions based on large-scale data inputs.

This book provides an introduction to recent developments in automated stratigraphic correlation of fossil data, using computer programs for ranking and scaling of stratigraphic events.

Cooperative Control of Multi-Agent Systems: An Optimal and Robust Perspective reports and encourages technology transfer in the field of cooperative control of multi-agent systems.

Quickly detect, troubleshoot, and prevent a wide range of data issues through data observability, a set of best practices that enables data teams to gain greater visibility of data and its usage.

The book focuses on how machine learning and the Internet of Things (IoT) has empowered the advancement of information driven arrangements including key concepts and advancements.

This book provides a comprehensive exploration of Industry 6.

Develop informative and aesthetic visualizations that enable effective data analysis in less timeKey FeaturesDiscover structure of ggplot2, grammar of graphics, and geometric objectsStudy how to design and implement visualization from scratchExplore the advantages of using advanced plotsBook DescriptionApplied Data Visualization with R and ggplot2 introduces you to the world of data visualization by taking you through the basic features of ggplot2.

Effective visualization is the best way to communicate information from the increasingly large and complex datasets in the natural and social sciences.

Discover how to use Neo4j to identify relationships within complex and large graph datasets using graph modeling, graph algorithms, and machine learningKey FeaturesGet up and running with graph analytics with the help of real-world examplesExplore various use cases such as fraud detection, graph-based search, and recommendation systemsGet to grips with the Graph Data Science library with the help of examples, and use Neo4j in the cloud for effective application scalingBook DescriptionNeo4j is a graph database that includes plugins to run complex graph algorithms.

Applied Analysis of Composite Media: Analytical and Computational Approaches presents formulas and techniques that can used to study 2D and 3D problems in composites and random porous media.

The Esri Guide to GIS Analysis, Volume 3: Modeling Suitability, Movement, and Interaction describes practical applications of modeling concepts in a geographic information system (GIS).

This unique textbook intersects traditional library science with data science principles that readers will find useful in implementing or improving data services within their libraries.

A Tour of Data Science: Learn R and Python in Parallel covers the fundamentals of data science, including programming, statistics, optimization, and machine learning in a single short book.

Integrate open source data analytics and build business intelligence on SQL databases with Apache Superset.

Health care utilization routinely generates vast amounts of data from sources ranging from electronic medical records, insurance claims, vital signs, and patient-reported outcomes.

Many organizations today analyze and share large, sensitive datasets about individuals.

Nowadays, finance, mathematics, and programming are intrinsically linked.

Machine learning is an intimidating subject until you know the fundamentals.

Data Scientists are experts at analyzing, modelling and visualizing data but, at one point or another, have all encountered difficulties in collaborating with or delivering their work to the people and systems that matter.

Wearable Sensing and Intelligent Data Analysis for Respiratory Management highlights the use of wearable sensing and intelligent data analysis algorithms for respiratory function management, offering several potential and substantial clinical benefits.

Mikhail Zhilkin, a data scientist who has worked on projects ranging from Candy Crush games to Premier League football players' physical performance, shares his strong views on some of the best and, more importantly, worst practices in data analytics and business intelligence.

From controlling disease outbreaks to predicting heart attacks, dynamic models are increasingly crucial for understanding biological processes.

This concise, easy-to-use reference puts one of the most popular frameworks for deep learning research and development at your fingertips.

Databases for Data-Centric Geotechnics forms a definitive reference and guide to databases in geotechnical and rock engineering, to enhance decision-making in geotechnical practice using data-driven methods.