White-box models in machine learning offer greater transparency and interpretability compared to black-box models, making them more suitable for critical applications.

This requires basic machine learning literacy — what kinds of problems can machine learning solve, and how to talk about those problems with data scientists. Linear regression and feature ...

The insurer will use Akur8’s Core Platform, which leverages proprietary ML technology to improve pricing processes.

Advancing Interpretability in Machine Learning: Model Summaries and Interpretable Regional Descriptors Susanne Dandl * 1, Marc Becker 2, Bernd Bischl 1, Giuseppe Casalicchio 2, ... The package draws ...

Duration: 12h. In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial ...

Development of a machine learning-based multivariable prediction model for the naturalistic course of generalized anxiety disorder. Journal of Anxiety Disorders , 2025; 110: 102978 DOI: 10.1016/j ...

Logistic regression is a particular case of a generalized linear model. Like linear regression, logistic regression is a widely used statistical tool and one of the foundational tools for your data ...

Understand what is Linear Regression Gradient Descent in Machine Learning and how it is used. Linear Regression Gradient Descent is an algorithm we use to minimize the cost function value, so as ...