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

  1. understanding the interesting game concepts,
  2. finding the relevant features for the classification model
  3. resolving the skewness in data
  4. Failed to come up with a very satisfying model

Accomplishments that we're proud of

  1. Data Visualization and successful implementation of different classification models to distinguish between spending player over non-spending players..
  2. Followed PEP 8 standard
  3. Learnt about infrastructure setup.

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