Inspiration
We were inspired to create Carseek after witnessing one of my friends struggle to sell their car for an arbitrary price due to a lack of information on correct prices for their vehicles, prompting them to seek assistance from various people and sources, only to run into price issues themselves, resulting in them selling for a much lower price.
What it does
Our web application assists users in predicting car prices by taking inputs such as the model, price range when purchasing, mileage offered now, and other factors, based on which it calculates the most accurate average price for the same and displays the results in the form of a graph, allowing even those who are not tech-savvy to benefit.
How we built it
We built the application using Flask in the backend, Python and its libraries in the front-end. Also, we used jinja and other languages for building the application.
Challenges we ran into
We had trouble figuring out how to connect the backend with the frontend.
Accomplishments that we're proud of
We made the website and figured out how to use machine learning for easy and accurate calculation of car prices taking into account all other factors.
What we learned
We learned how to use jinja and flask as all our members were new to this.
What's next for Carseek
We plan on connecting the calculating functions to the website. We envision performing the data scrapping from the used car selling postings such as a Facebook marketplace and showing the simulation about price graph.
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