Car Price Predictor App used to predict the price of the car based on certain input parameters created using python's scikit-learn, fastapi, numpy and joblib packages.

Related tags

Deep LearningPricefy
Overview

Pricefy

made-with-python python 3.9.7 html python numpy pandas scikit-learn fastapi heroku vscode

Car Price Predictor App used to predict the price of the car based on certain input parameters created using python's scikit-learn, fastapi, numpy and joblib packages.

Dataset Description :-

This dataset contains information about used cars. This data can be used for a lot of purposes such as price prediction to exemplify the use of linear regression in Machine Learning.

The data contains the following columns:

Feature Name Feature Description
Name Name of the Car model
Present_Price Present showroom price of the car
Year Car Model Year
Kms_Driven Kilometers driven till now
Owner No of Owners (0 or 1 or 2 or 3)
Fuel_Type Type of Fuel (Petrol or Diesel or CNG)
Seller_Type Whether seller is (Individual or Dealer)
Transmission Transmission type (Automatic or Manual)
Selling_Price Used Car selling price (Target) variable

Installation :-

Open Anaconda prompt and create new environment 👇 

conda create -n your_env_name python = (any_version_number)

Then Activate the newly created environment 👇 

conda activate your_env_name

To install all requirement packages for the app 👇 

pip install -r requirements.txt

Then, Run the app 👇 

uvicorn main:app --reload

📷 Screenshots:-

Home page:-

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About section:-

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Developer section:-

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Swagger UI:-

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Redoc UI:-

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Demo GIF Image 👇 :-

demo_gif

Owner
Siva Prakash
I am a final year BCA student who more fascinated about data analysis and machine learning.
Siva Prakash
GitHub Repository https://pricefy.herokuapp.com/
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