Keep it simple.

What it does

Predicts the next three months of demand for the products based on historical data.

How we built it

  • Scikit learn model trains on historical data and predicts next three months unit sales
  • Flask server to serve results from model to UI
  • UI in Vue JS for visualization results additional to the generated csv with predictions

Challenges we ran into

  • Model training time
  • Feature engineering wasn't working
  • Linear regression model had a very low R2 score, so we opted for

Accomplishments that we're proud of

  • 31.09 MSE
  • 81.72% R2 Score on Holdout Set
  • Successful predictions exported as CSV

What we learned

  • Technologies used
  • Feature Engineering

What's next for 70 On-Demand

  • Create temperature and sunshine conditions to be able to predict demand at any point in the future
  • Random forest is our baseline, so we expect neural network will outperform with the features used.

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