The goal of this project is to create a Python class that performs linear regression using gradient descent. The class handles feature normalization, computes the cost function, updates the model ...

Gradient descent is a fundamental optimization technique used in training a wide range of machine learning models, including linear regression, logistic regression, neural networks, and many others.

The cost function minimization is essential in finding a good model for linear regression. This paper works on prototyping and examining the minimizing cost function's two known algorithms for online ...

Understand what is Linear Regression Gradient Descent in Machine Learning and how it is used. Linear Regression Gradient Descent is an algorithm we use to minimize the cost function value, so as ...

Linear regression is the simplest machine learning technique to predict a single ... a model is usually trained using iterative stochastic gradient descent (SGD), which requires a learning rate and a ...

On this type of balance data, linear Regression performs good but what if the data is imbalanced. Now apply linear Regression on imbalanced data and analyze the predictions. You will see that linear ...