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Tag Archives: ML-Regression

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
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
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
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
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
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
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
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