Inspiration
We are all passionate about learning data science and Fantasy Sports so we decided to choose this challenge to focus on.
What it does
Classifies users as bots based on login timing and frequency, classifies users into risk buckets based on individual spending
How we built it
We worked in a Jupyter Notebook on Google Colab, mainly using Pandas in Python and SQL Queries.
Challenges we ran into
As beginners, it was quite the learning curve, and a lot of time was spent figuring out things we initially may have thought to be trivial.
Accomplishments that we're proud of
Having spent a lot of time creating a functional bot classification system based on session duration times, this system should dramatically increase the experience for real users. In addition, we were able to classify users based on the amount of risk is involved in each bet. It was quite a busy time for each of us, having multiple midterms scheduled in the upcoming week and each being concerned with our own job applications and time schedules, but we were still able to schedule and execute meetings online, finding times where each of us are available. Dividing the work was very successful, working around each person's individual strengths.
What we learned
How to organize, plan, execute and troubleshoot a large data science project in a team How to work together in Colab, how to use SQL Queries and Pandas to modify and classify data
What's next for Crackers
More Data Science Hackathons, side projects, and learning :))
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