What are Support Vector Machines?

What are Support Vector Machines?

Support Vector Machines (SVMs) are a type of Supervised Learning algorithm that can be used for both classification and regression tasks. They are particularly useful for problems with high-dimensional data and complex decision boundaries. History SVMs were first introduced in the early 1990s by Vladimir Vapnik and his colleagues at Bell Labs. They were initially…

Logistic Regression in Machine Learning: What is it?

Logistic Regression in Machine Learning: What is it?

Logistic regression is a popular algorithm used in supervised learning for classification tasks. Supervised learning is a method of machine learning that involves training a model on a labeled dataset, where the inputs and corresponding outputs are already known. In this article, we will discuss the basics of logistic regression, its applications, and how it…

Linear Regression in Machine Learning: What is it?

Linear Regression in Machine Learning: What is it?

Linear regression is a supervised learning algorithm that is used to analyze the relationship between a dependent variable and one or more independent variables. It is a widely used method in machine learning and statistics for both simple and multiple linear regression. The goal of linear regression is to find the best-fitting line that represents…