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Sales Forecasting
I developed a comprehensive sales forecast, analyzing sales data from restaurant inception to the end of 2022 using the Prophet library by Meta. The model's accuracy was measured by multiple metrics, demonstrating fair predictive performance:
Mean Absolute Error: $1,236.26
Mean Absolute Percentage Error: 2.18%
Correlation: 0.937
R-Squared: 0.87
Bias: 10.55
Inventory Dashboard
Using a custom Python script, I parsed the .csv files of sales data to translate ingredient usage data into actionable insights. This assisted in calculating par levels and identifying trends of popularity over multiple time frames.
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