This a simple car price prediction model that I build for demonstration purpuose to the GDSC members.
I found the dataset on Kaggle, I took a lot of techniques from kaggle notebooks to build the model and deployed the model using flask.
For the front-end I have used HTML and CSS
This is how it looks and works
---- results
| |---- car_price_prediction.gif
| |
| |---- webapp.png
|
|---- static
| |---- images
| | |---
| |
| |---- styles
| | |
| | |---- index.css
|
|---- templates
| |---- index.html
| |
|
|---- app.py
|
|---- car_price_prediction.ipynb
|
|---- model.pkl
|
|---- README.md
|
|----requirements.txt
- python library - numpy, pandas, seaborn, matplotlib, sklearn
- version control - git
- backend - flask
- IDE - Vs code
To build this project I have reffered to the following videos on YouTube :