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Learning predictive analytics with python : gain practical insights into predictive modelling by implementing Predictive Analytics algorithms on public datasets with Python

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GitHub

Python codes for performing life cycle assessment (LCA) scenario analyses, sensitivity analyses, and Monte Carlo analyses, using systems of equations and variable input parameters

Parametric LCA aims to maintain the relationships between different parameters along the life cycle of a system or product, modeling the system with variables and equations that depict these ...
GitHub

Estimating and Exploiting the Aleatoric Uncertainty in Surface Normal Estimation

The proposed method estimates the per-pixel surface normal probability distribution, from which the expected angular error can be inferred to quantify the aleatoric ...
thetechedvocate.org

How to calculate probability distribution

Probability distribution is an essential concept in statistics, helping us understand the likelihood of different outcomes in a random experiment. Whether you’re a student, researcher, or professional ...
Visual Studio Magazine

Wasserstein Distance Using C# and Python

The Data Science Lab Wasserstein Distance Using C# and Python Dr. James McCaffrey of Microsoft Research shows how to compute the Wasserstein distance and explains why it is often preferable to ...
Frontiers

Bayesian Generalized Linear Model for Simulating Bacterial Inactivation/Growth Considering Variability and Uncertainty

Predictive microbiology models explain bacterial number variations over time and how growth/inactivation rates are affected by environmental conditions (Lammerding and Fazil, 2000). In the development ...