Inspiration
What it does
Our project utilizes k means in order to correlate the data and create personalized challenges for the clients to participate whilst they shop for products.
How we built it
We analyzed the data by creating a program that first joined the data of 2022 and 2023 in one file. We got rid of all blank and invalid values. Afterwards, the k mean cluster technique was used to correlate numeric data and be able to assign challenges for the clients.
Challenges we ran into
Given that most of our teamate are inexperienced, it was really hard for us to get started. The cleaning and reformatting of data took a long time, which ended up with us not being able to fully develop our project.
Accomplishments that we're proud of
All of our group members are second semester students, so we don't really have enough coding experience. This made the most important things such as compiling data, a bit hard to do since we don't have enough knowledge.
What we learned
We learned to work as a team to figure out our shortcomings.
What's next for Reto 4-Equipo Bug Busters
Next, we would wish to be able to finish the program fully.
Built With
- google-colab
- python
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