Measuring the abundance of individuals and the diversity of species are core components of most ecological research projects and conservation monitoring.
Leading tech companies such as Netflix, Amazon and Uber use data science and machine learning at scale in their core business processes, whereas most traditional companies struggle to expand their machine learning projects beyond a small pilot scope.
Presents an analysis and visualization of social networks integrating theory, applications, and professional software for performing network analysis (Pajek).
Examines a set of voter information campaigns worldwide to assess their effectiveness, and develops a new social science research model aimed at cumulative learning.
Research Data Management (RDM) has become a professional topic of great importance internationally following changes in scholarship and government policies about the sharing of research data.
Question answering (QA) systems on the Web try to provide crisp answers to information needs posed in natural language, replacing the traditional ranked list of documents.
Jump-start your career as a data scientist learn to develop datasets for exploration, analysis, and machine learning SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis is a resource that s dedicated to the Structured Query Language (SQL) and dataset design skills that data scientists use most.
Focus on Geodatabases in ArcGIS Pro introduces readers to the geodatabase, the comprehensive information model for representing and managing geographic information across the ArcGIS platform.
Crime research has grown substantially over the past decade, with a rise in evidence-informed approaches to criminal justice, statistics-driven decision-making and predictive analytics.
A practical introduction to network science for students across business, cognitive science, neuroscience, sociology, biology, engineering and other disciplines.
Leading tech companies such as Netflix, Amazon and Uber use data science and machine learning at scale in their core business processes, whereas most traditional companies struggle to expand their machine learning projects beyond a small pilot scope.
The correct design, analysis and interpretation of plant science experiments is imperative for continued improvements in agricultural production worldwide.
This practical textbook offers a hands-on introduction to big data analytics, helping you to develop the skills required to hit the ground running as a data professional.
Jump-start your career as a data scientist learn to develop datasets for exploration, analysis, and machine learning SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis is a resource that s dedicated to the Structured Query Language (SQL) and dataset design skills that data scientists use most.
Introduces biological concepts and biotechnologies producing the data, graph and network theory, cluster analysis and machine learning, using real-world biological and medical examples.
In an age where customer opinion and feedback can have an immediate, major effect upon the success of a business or organization, marketers must have the ability to analyze unstructured data in everything from social media and internet reviews to customer surveys and phone logs.
