# Tag Archives: ML-Regression

## Implementation of Ridge Regression from Scratch using Python

Prerequisites: Linear Regression Gradient Descent Introduction: Ridge Regression ( or L2 Regularization ) is a variation of Linear Regression. In Linear Regression, it minimizes the… Read More »

## Implementation of Elastic Net Regression From Scratch

Prerequisites:  Linear Regression Gradient Descent Lasso & Ridge Regression Introduction:  Elastic-Net Regression is a modification of Linear Regression which shares the same hypothetical function for… Read More »

## Implementation of Lasso Regression From Scratch using Python

Prerequisites:  Linear Regression Gradient Descent Introduction:  Lasso Regression is also another linear model derived from Linear Regression which shares the same hypothetical function for prediction.… Read More »

## XGBoost for Regression

The results of the regression problems are continuous or real values. Some commonly used regression algorithms are Linear Regression and Decision Trees. There are several… Read More »

Logistic regression is a classification algorithm used to find the probability of event success and event failure. It is used when the dependent variable is… Read More »

## Solving Linear Regression in Python

Linear regression is a common method to model the relationship between a dependent variable and one or more independent variables. Linear models are developed using… Read More »

## COVID-19 Peak Prediction using Logistic Function

Making fast and accurate decisions are vital these days and especially now when the world is facing such a phenomenon as COVID-19, therefore, counting on… Read More »

## Polynomial Regression for Non-Linear Data – ML

Non-linear data is usually encountered in daily life. Consider some of the equations of motion as studied in physics. Projectile Motion: The height of a… Read More »

## Implementation of Lasso, Ridge and Elastic Net

In this article, we will look into the implementation of different regularization techniques. First, we will start with multiple linear regression. For that, we require… Read More »