Because the linear ridge regression training algorithm presented in this article inverts a matrix, the technique doesn't scale to problems with huge amounts of training data. In such situations, it is ...

In this academic project, we implemented and compared betwen regression methods for linear, multi-linear and exponential problems. For the linear case, the implemented algorithms are : Newton method, ...

We will now implement Simple Linear Regression using PyTorch. Let us consider one of the simplest examples of linear regression, Experience vs Salary. We will train a regression model with a given set ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of linear regression with two-way interactions between predictor variables. Compared to standard linear ...

A set of differential equations describing the dynamics of the transmission system and connected machines, including the voltage regulators and governors, is formed. The terms of these equations are ...

Multiple Linear Regression¶ 9.1. Preliminaries¶ As before, we need to start by: Loading the Pandas and Statsmodels libraries. Reading the data from a CSV file. Fixing the column names using Panda’s ...

This brief deals with the problem of robust exponential stabilization of a class of time-delay systems using sliding-mode controllers. Continuous controllers are synthesized to guarantee that the ...

Learn how to choose between linear and nonlinear regression models for your data analysis, based on fit, inference, and simplicity criteria. Agree & Join LinkedIn ...

This repository includes the C language implementation of some fundamental operations such as FFT, matrix inverse, matrix-vector multiplication, linear regression, 1D convolution and determinant of a ...