PC Tech Magazine

Advanced AI and ML Courses to Learn Machine Learning, Deep Learning in 2026

Most working professionals already understand that AI skills are no longer optional they are a career necessity.
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 ...
Visual Studio Magazine

Quadratic Regression with SGD Training Using C#

Quadratic regression extends linear regression by adding squared terms and pairwise interaction terms, enabling the model to capture non-linear structure and predictor interactions. The article ...
GitHub

AI-Based Inference System for Concrete Compressive Strength: Multi-dataset Analysis of Optimized Machine Learning Algorithms

The prediction of concrete compressive strength (CS, MPa) is fundamental in experimental civil engineering, as it enables the optimization of mix design and complements laboratory testing through ...
Nature

Using multiple linear regression to predict engine oil life

This paper deals with the use of multiple linear regression to predict the viscosity of engine oil at 100 °C based on the analysis of selected parameters obtained by Fourier transform infrared ...
Scientific Research Publishing

Hourly Soil Temperature Variability and Estimation at Multiple Depths from Meteorological Data Using Multiple Linear Regression in a Tropical Semi-Arid Region of Burkina Faso ()

Accurate estimation of soil temperature is essential for understanding land–atmosphere interactions and supporting agricultural management in semi-arid regions. This study focuses on the analysis of ...
IEEE

Machine Learning-Based Approaches and Comparisons for Estimating Missing Meteorological Data and Determining the Optimum Data Set in Nuclear Energy Applications

Abstract: Good data analysis is required for the optimal design of nuclear energy projects. However, due to financial or technical reasons, data cannot be collected regularly, which leads to missing ...
Nature

Comprehensive study on the Python-based regression machine learning models for prediction of uniaxial compressive strength using multiple parameters in Charnockite rocks

Rocks and their structures require careful planning to prevent loss of life and economic damage from human error. In civil engineering, mining, cave mining, tunneling ...
GitHub

On Breast Cancer Detection: An Application of Machine Learning Algorithms on the Wisconsin Diagnostic Dataset

Note: This repository is retired and will not be ported to use TF2. However, you may use this as a reference in doing so. This paper was presented at the 2nd International Conference on Machine ...
C&EN

Sparse Gaussian Process Regression-Based Machine Learned First-Principles Force-Fields for Saturated, Olefinic, and Aromatic Hydrocarbons

Center for Superfunctional Materials, Department of Chemistry, Ulsan National Institute of Science and Technology, 50 UNIST-gil, Ulsan 44919, Korea Article Views are the COUNTER-compliant sum of full ...