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With the increasing prevalence of big data and sparse data, and rapidly growing data-centric approaches to scientific research, students must develop effective data analysis skills …
Many real-life systems are dynamic, evolving, and intertwined. Examples of such systems displaying 'complexity', can be found in a wide variety of contexts ranging from economics …
Privacy-preserving computing aims to protect the personal information of users while capitalizing on the possibilities unlocked by big data. This practical introduction for …
Presenting the fundamental algorithms and data structures that power bioinformatics workflows, this book covers a range of topics from the foundations of sequence analysis …
In this comprehensive, accessible work, Ross P. Buckley, Douglas W. Arner, and Dirk A. Zetzsche offer an ideal reference for anyone seeking to understand the technological …
The book offers a succinct overview of the technical components of blockchain networks, also known as distributed digital ledger networks. Written from an academic perspective, it …
Big data and algorithmic decision-making have been touted as game-changing developments in management research, but they have their limitations. Qualitative approaches should not …
Statistical and machine learning methods have many applications in the environmental sciences, including prediction and data analysis in meteorology, hydrology and oceanography; …