[Carsome Challenge 1] Car Pricing Prediction

Inspiration

For my first machine learning model, I built the algorithm that estimates the car price with a decision tree model and deployed it to the web environment.

What it does

This web application is simple to use, where the user just needs to input the information about the car that they want to buy and the web application will give them the estimated price.

How we built it

This model is built in Jupyter Notebook with Jolib support to save the trained model and deploy it in a web environment by Streamlit.

Challenges we ran into

I got a challenge with the design of my web application as now it is very simple. In the future, I will try to make it user-friendly and with a more professional look and feel.

Accomplishments that we're proud of

I am proud that I have done my first machine learning model and my first hackathon.

What we learned

I learning about how to choose the best machine learning model and learning how to deploy it.

What's next for [Carsome Challenge 1] Car Pricing Prediction

• Test and try with more machine learning algorithms.
• Improve UI/UX design of the web application.
• Let the model learn on different datasets.

Built With

• joblib
• jupyter
• pandas
• python
• sklearn
• streamlit