Introduction In this post we will try to understand about regularization and hyperparameter-tuning using Ridge and Lasso Regression. Before that we need to understand few concepts of Linear Regression. I will provide a brief explanation here which would suffice our motive of this topic, however if you want to get a more in-depth understanding of…Read more

# Linear Regression

## Math behind Simple Linear Regression

Simple Linear Regression In this post we will try to understand the Math behind Simple Linear Regression. But before getting into the details let’s understand what Simple Linear Regression means. Simple Linear Regression basically defines relationship between one feature and a continuous outcome variable/ dependent variable y = α +βx. This equation is similar to the…Read more

## Mathematical assumptions while solving problems using Regression

Introduction Understanding the math behind any algorithm is very important. Often we dive straight into solving a problem using some machine learning algorithm and applying all sorts of techniques without understanding the underlying fundamentals of the algorithm, the assumptions that should be taken while implementing it on a particular scenario etc.In this post, we will…Read more

## Linear Regression

The figure that you are seeing above details the various steps in data preprocessing as well as the Linear regression. We have covered the data preprocessing steps in detail here. In this post we will be going over in detail on the lower portion of the figure which is the Linear Regression. Regression Before getting…Read more

## Simple Linear Regression

Introduction What is Simple Linear Regression Simple Linear Regression basically defines the relation between a one feature and the outcome variable. This can be specified using the formula y = α + βx which is similar to the slope-intercept form, where y is the value of the dependent variable, α is the intercept β denotes…Read more