I spent the last week of March 2026 in San Francisco talking to CTOs, CPOs, and engineering leaders from companies of every ...

We will use a dataset on high school students’ choice of academic program (general, academic, vocational) to illustrate the methods. Binary logistic regression ...

In [Part 1](https://github.com/pw2/STAN-Blog-Tutorials/blob/main/STAN%20Part%201%20-%20Intro%20to%20STAN%20Code.Rmd) we laid the ground work for coding in `STAN` and ...

We will build a Regression Language Model (RLM), a model that predicts continuous numerical values directly from text sequences in this coding implementation. Instead of classifying or generating text ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the random forest regression technique (and a variant called bagging regression), where the goal is to ...

Large Language Models (LLMs) have revolutionized data analysis by introducing novel approaches to regression tasks. Traditional regression techniques have long relied on handcrafted features and ...

Abstract: This tutorial aims to provide an intuitive introduction to Gaussian process regression (GPR). GPR models have been widely used in machine learning applications due to their representation ...

Non-linear regression modeling is common in epidemiology for prediction purposes or estimating relationships between predictor and response variables. Restricted cubic spline (RCS) regression is one ...