We wanted to learn how targeted marketing works on a fundamental level, such as YouTube and Facebook recommendations.
What it does
Lap-a-Top prompts the user for laptop usage and spec preferences through the Python console, and recommends up to 10 laptops that it ranks as best based on an algorithm, using user responses as input.
How I built it
First we scraped laptop data from Newegg.com, cleaned it into usable form, then built a user interaction system, as well as a simple data analysis system to take user input and recommend laptops.
Challenges I ran into
The two biggest challenges were deciding how to transform raw data into a usable and useful format, as well as deciding on an algorithm to rank laptops.
Accomplishments that I'm proud of
I learned a lot about data manipulation in Python using pandas, overcame countless frustrations and debugging, and successfully collaborated with 2 brand-new team members who all contributed together.
What I learned
Patience is a virtue.
What's next for Lap-a-Top
We'd like to scrape more data to make our dataset more complete, as well as convert it into a web application.