[Linear Regression] Complete Theory And Mathematics With Example 2021 Urdu/Hindi

I can do your assignments projects quizzes etc in very low price
www.fiverr.com...
Linear regression is used for finding linear relationship between target and one or more predictors. There are two types of linear regression- Simple and Multiple.
The core idea is to obtain a line that best fits the data. The best fit line is the one for which total prediction error (all data points) are as small as possible. Error is the distance between the point to the regression line.
Optimizing using gradient descent:
In linear regression, the model targets to get the best-fit regression line to predict the value of y based on the given input value (x). While training the model, the model calculates the cost function which measures the Root Mean Squared error between the predicted value (pred) and true value (y). The model targets to minimize the cost function.
To minimize the cost function, the model needs to have the best value of θ1 and θ2. Initially model selects θ1 and θ2 values randomly and then itertively update these value in order to minimize the cost function until it reaches the minimum. By the time model achieves the minimum cost function, it will have the best θ1 and θ2 values. Using these finally updated values of θ1 and θ2 in the hypothesis equation of linear equation, model predicts the value of x in the best manner it can.
Difference between regression and classification:
• Difference between cla...
Machine learning series:
• MACHINE LEARNING TUTOR...
Complete python tutorials:
• python tutorial for be...
Facebook Page:
/ tec9port