Problem Statement
Build a Linear_Regression_Model to Predict House Price and Visualizing the Following
- ->Residuals
- ->Distribution of Error
- ->Model Coefficience
- Project URL: PowerBI-project
Project Approch and Solution:
Using Pandas we import the csv file from Local system, After import the Data to the notebook we check where the Imported data is Correctly imported or is there any nesseary changes to done to get correct data, next step after that would be Checking for missing data in the dataset, and Try to fill that data by using mean and Median to fill the missing values based on the column or If that less then drop those rows, There are few other step carred to Train the model, befor that we need to Seperate the Dependent and Target varible separately.
The Approch Which i have use here is use of scatter plot for Residuals, Use of Histogram to represent the Distribution of errors, And Horizental barchart to Model Coefficients.
Solution:
Check the Complete Solution: ->>>Here<<<-