Resources to learn Linear Regression


In this blog post, I’ll be sharing functional, informative, and relevant content on data science from the internet amalgamated with my own knowledgeable insights on the topic “Linear Regression.” So, without further ado let’s get into it.

1. Linear Regression in Machine Learning (from Scratch !!)

As per Wikipedia, Regression Analysis is defined as a set of statistical processes used to estimate the strength of the relationship between a dependent variable and an independent variable. The process which tries to estimate this strength of relationship assuming a linear behavior between the dependent and independent variable is called Linear Regression. 

Categories: Machine Learning, Python, Statistics, Supervised Learning

Level: Beginner

Link to the entire article:


2. Linear Regression with Python Implementation

In Supervised Learning, we will have both the independent variable (predictors) and the dependent variable (response). Our model will be trained using both independent and dependent variables. So we can predict the outcome when the test data is given to the model. Here, using the output our model can measure its accuracy and can learn over time.

Categories: Machine Learning, Python

Level: Beginner

Link to the entire article:


3. How a Math equation is used in building a Linear Regression model?

Let us get much deeper now. From our school days, we have come across the equation of the straight line i.e. y = mx + c, right? Haven’t we? Yes, we have in fact, a lot many times. Do you know that this one equation helps in building a linear regression model in the machine learning world? Yes, you heard it right. The entire Linear regression is built on this equation.

Categories: Machine Learning, Maths, Python, Regression

Level: Intermediate

Link to the entire article:


4. Everything you need to Know about Linear Regression!

Linear regression is a quiet and the simplest statistical regression method used for predictive analysis in machine learning. Linear regression shows the linear relationship between the independent(predictor) variable i.e. X-axis and the dependent(output) variable i.e. Y-axis, called linear regression.

Categories: Guide, Linear Regression, Machine Learning, R

Level: Beginner

Link to the entire article:


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