Statistical modeling lies at the heart of data science. Well-crafted statistical models allow data scientists to draw conclusions about the world from the limited information present in their data. In ...

This technical FAQ examines three modeling gaps identified in engineering literature and outlines algorithmic methods to ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric ...

Sparse data can impact the effectiveness of machine learning models. As students and experts alike experiment with diverse datasets, sparse data poses a challenge. The Leeds Master’s in Business ...

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...

The Covid-19 pandemic reminded us that everyday life is full of interdependencies. The data models and logic for tracking the progress of the pandemic, understanding its spread in the population, ...

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...

Microbiome sequencing data are known to be biased; the measured taxa relative abundances can be systematically distorted from their true values at every step in the experimental/analysis workflow. If ...