Inspiration
Our interest in Game Development and Machine learning inspired us to work on Game analytics.
What it does
The web application is used to predict how likely a player is willing to spend upon downloading apps.
Python was the primary language used in this project. We used various Python libraries such as Scikit-learn, Pandas, Numpy, Matplotlib, etc.. for data analysis, classification and visualization.
Conda was used to create the virtual environment.
Challenges we ran into
- understanding the interesting game concepts,
- finding the relevant features for the classification model
- resolving the skewness in data
- Failed to come up with a very satisfying model
Accomplishments that we're proud of
- Data Visualization and successful implementation of different classification models to distinguish between spending player over non-spending players..
- Followed PEP 8 standard
- Learnt about infrastructure setup.
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