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Hey there! Welcome to Chapter 1 on Data Preprocessing! Before getting into Machine Learning, let me tell you what you'll need: Educational requirement: Just some high school math, DSA (in python) (Probability and statistics will help you a lot. I ...
Welcome to Part 2 - Regression! Regression models (both linear and non-linear) are used for predicting a real value, like salary for example. If your independent variable is time, then you are forecasting future values, otherwise your model is predic...
Welcome to Part 2.2 of Machine Learning! Here is the equation for multiple linear regression. As you can see, it is quite similar to our linear regression model. Assumptions of linear regression Now, let's look at the first dataset for the linear re...
Welcome back to Machine Learning! Today we’ll talk about Polynomial Regression Polynomial Regression Intuition If you look carefully, polynomial regression is very similar to the multiple linear regression. But, instead of different variable, x1 is d...
Welcome to Machine Learning! Support vector regression was created in the 90s by Vladimir Vapnik and his team at Bell Labs, which was known as AT&T Bell Labs back then. But for now, we'll focus just on linear regression. Let's get started! SVR Intuit...
Welcome to another blog on Machine Learning! Today we are going to have a look at the Decision Tree Regression. Intuition There is a term called CART which stand for classification and regression tree. In this blog we’ll talk mostly about regression ...
