Pricefy 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.
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 |
Open Anaconda prompt and create new environment
conda create -n your_env_name python = (any_version_number > 3.10.4)
Then Activate the newly created environment
conda activate your_env_name
Clone the repository using git
git clone https://github.com/Prakashdeveloper03/Pricefy.git
Change to the cloned directory
cd <directory_name>
To install all requirement packages for the app
pip install -r requirements.txt
Then, Run the app
uvicorn main:app --reload
