Housing-Price-prediction # Project 1

Trying to Predic housing prices Using Linear Regression Model and Sklearn

coeff (How An Increase In Various Factors Affects The Pricing)

area 3.385669e+02 bedrooms 1.837452e+05 bathrooms 1.119619e+06 stories 5.295595e+05 parking 4.136710e+05

The mean_absolute_error of the Model of y_test and predictionsis :

897128.5810529626 #The mean_squared_error(y_test,predictions) : 1536187446070.5046

The Root mean_squared_error :

1239430.2909282574

The Dataset Can be found at https://www.kaggle.com/datasets/ashydv/housing-dataset?resource=download

Evaluating Whether an app Or a Website Will Have more Customers #2

coeff

An Increse in Avg. Session Length Will increase a revenue of ($ 25.691540 ) An Increse on Time on App Increses Revenue By ( $ 37.892600 ) An Increse on Time on Website Increases Revenue By ( $ 0.560581 ) An increase in Length of Membership increases Revenue By ( $ 61.648594 )

Models Metrics