GitHub

machine-learning-for-physics

Machine learning project predicting sleep quality using Linear Regression, Random Forest, and Neural Networks with TensorFlow/Keras. Includes tutorial notes and full analysis.
Hosted on MSN

Tutorial - How do we solve a system of linear equations using any method

Learn how to solve a system of equations by using any method such as graphing, elimination, and substitution. 1/2 x + 2/3 y = 5/6, 5/12 x + 7/12 y = 3/4 Heavy snow warning as up to 30 inches to strike ...
Analytics Insight

Best Neural Networks Courses in 2026 for AI and Deep Learning

Neural networks courses in 2026 focus heavily on practical deep learning frameworks such as TensorFlow, PyTorch, and Keras. Growing demand for AI professionals has significantly increased enrollment ...
marktechpost

A Coding Implementation to Establish Rigorous Prompt Versioning and Regression Testing Workflows for Large Language Models using MLflow

In this tutorial, we show how we treat prompts as first-class, versioned artifacts and apply rigorous regression testing to large language model behavior using MLflow. We design an evaluation pipeline ...
Visual Studio Magazine

Linear Regression with Pseudo-Inverse Training Using JavaScript

Linear regression is the most fundamental machine learning technique to create a model that predicts a single numeric value. One of the three most common techniques to train a linear regression model ...
IEEE

Shuffled Linear Regression via Spectral Matching

Abstract: Shuffled linear regression (SLR) seeks to estimate latent features through a linear transformation, complicated by unknown permutations in the measurement dimensions. This problem extends ...
Visual Studio Magazine

Linear Regression Using JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...
Scientific Research Publishing

Harrell, Jr. (2015) Regression Modeling Strategies with Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis. 2nd Edition, Springer.

ABSTRACT: There is a set of points in the plane whose elements correspond to the observations that are used to generate a simple least-squares regression line. Each value of the independent variable ...
IEEE

Tensor Decomposition-Based Relaxed Linear Regression for Hyperspectral Image Classification

Abstract: Linear regression and its variants have achieved considerable success in image classification. However, those methods still encounter two challenges when dealing with hyperspectral image ...