In Week 11, I explained the difference between anticipated regression and the so-called "Gambler's fallacy", and in Week 12, ...

Objective To examine whether a multicomponent commercial fitness app with very small (‘micro’) financial incentives (FI) ...

Introduction Armed conflict severely impacts health, with indirect deaths often exceeding direct casualties two to four times ...

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.

Discover how multivariate models use multiple variables for investment forecasting, risk analysis, and decision-making in finance. Ideal for portfolio management.

Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...

Anthropic is offering $5 worth of free API access to users and developers. You can start using the API for Opus and Sonnet models. However, API access for the smallest Haiku model is not available yet ...

Predicting performance for large-scale industrial systems—like Google’s Borg compute clusters—has traditionally required extensive domain-specific feature engineering and tabular data representations, ...

Abstract: Dyadic regression models, which output real-valued predictions for pairs of entities, are fundamental in many domains [e.g., obtaining user-product ratings in recommender systems (RSs)] and ...

What is linear regression in machine learning ? Understanding Linear Regression in machine learning is considered as the basis or foundation in machine learning. In this video, we will learn what is ...