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Welcome to the "Multiple Linear Regression Model for Predictive Analytics" repository! This project showcases the implementation of a Multiple Linear Regression model using Python for predictive analysis.

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Najrul-Ansari/Prediction-with-Multiple-Regression

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Prediction-with-Multiple-Regression

Tools -

Jupyter notebook, Python and its various libraries such as pandas, seaborn, matplotlib, sklearn,etc.

50 Startups ---

50 startup dataset conatins the data of 50 startups which has their spending on different departments anf the profit they have earned. The main objective of this project is to build a regression model to predict the profit of a startup on the basis of its spending on R&D ,Administration and Marketing. In this case the profit might differ for every startup on their decision of spending or how much spending in a particular department in order to earn maximum profit. The model build is about 92% accurate in predicting the profit of a startup given their spending in different department.

Toyota Corolla ---

Toyota Corolla dataset ia huge with 1436 rows and 38 columns but we were specified the columns on which we need to build our model, which eventually reduced the complexity in building the model. The model id quite accurate anf fit which can predict the price of a model on the basis of the required entry and gives a 87% accuracy rate.

Dataset Description -
Model -- model of the car
Price -- Offer Price in EUROs
Age_08_04 -- Age in months as in August 2004
Mfg_Month -- Manufacturing month (1-12)
Mfg_Year -- Manufacturing Year
KM -- Accumulated Kilometers on odometer
Fuel_Type -- Fuel Type (Petrol, Diesel, CNG)
HP -- Horse Power
Met_Color -- Metallic Color? (Yes=1, No=0)
Color -- Color (Blue, Red, Grey, Silver, Black, etc.)
Automatic -- Automatic ( (Yes=1, No=0)
cc -- Cylinder Volume in cubic centimeters
Doors -- Number of doors
Cylinders -- Number of cylinders
Gears -- Number of gear positions
Quarterly_Tax -- Quarterly road tax in EUROs
Weight -- Weight in Kilograms
Mfr_Guarantee -- Within Manufacturer's Guarantee period (Yes=1, No=0)
BOVAG_Guarantee -- BOVAG (Dutch dealer network) Guarantee (Yes=1, No=0)
Guarantee_Period -- Guarantee period in months
ABS -- Anti-Lock Brake System (Yes=1, No=0)
Airbag_1 -- Driver_Airbag (Yes=1, No=0)
Airbag_2 -- Passenger Airbag (Yes=1, No=0)
Airco -- Airconditioning (Yes=1, No=0)
Automatic_airco -- Automatic Airconditioning (Yes=1, No=0)
Boardcomputer -- Boardcomputer (Yes=1, No=0)
CD_Player -- CD Player (Yes=1, No=0)
Central_Lock -- Central Lock (Yes=1, No=0)
Powered_Windows -- Powered Windows (Yes=1, No=0)
Power_Steering -- Power Steering (Yes=1, No=0)
Radio -- Radio (Yes=1, No=0)
Mistlamps -- Mistlamps (Yes=1, No=0)
Sport_Model -- Sport Model (Yes=1, No=0)
Backseat_Divider -- Backseat Divider (Yes=1, No=0)
Metallic_Rim --Metallic Rim (Yes=1, No=0)
Radio_cassette -- Radio Cassette (Yes=1, No=0)
Tow_Bar -- Tow Bar (Yes=1, No=0)

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Welcome to the "Multiple Linear Regression Model for Predictive Analytics" repository! This project showcases the implementation of a Multiple Linear Regression model using Python for predictive analysis.

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