Analyzing student data on a large scale to find patterns in academic performance as they correlate with economic-background in order to identify which students need academic aid.
Inspired by previous learning experience to utilize and work with concepts of AI and machine learning.
## What it does
Analysis a data set and visualizes it to a series of graphs which help views draw conclusions based on observed patterns.
## How we built it
Using a data base from kaggle and basic AI concepts such as the basics of logistic regression to create models and graphs.
used information learned from previous learning experiences
## Challenges we ran into
this was out first hackathon as well as out first time applying concepts of AI to a project so we ran into several problems such as struggles with manipulating data.
## Accomplishments that we're proud of
being able to manipulate data and applying it to models was a huge accomplishment
## What we learned
learned a lot about building ideas and projects
## What's next for Student Data Analysis
being able to be more efficient and used in an even larger scale
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