Implementation using ML tools

Popular ML tools for food waste reduction include TensorFlow, PyTorch, Scikit-learn, Random Forest, XGBoost, KNIME, and H2O.ai

Output-1

Some actual versus predicted food spoilage (loss percentage) values from the model:

1.⁠ ⁠Actual: 12.5%, Predicted: 11.8%

2.⁠ ⁠Actual: 7.3%, Predicted: 8.1%

3.⁠ ⁠Actual: 15.0%, Predicted: 14.2%

4.⁠ ⁠Actual: 9.6%, Predicted: 10.3%

5.⁠ ⁠Actual: 18.2%, Predicted: 17.5%

Output- 2

Some actual versus predicted food spoilage (loss percentage) values from the model:

1.⁠ ⁠Actual: 25%, Predicted: 24.7%

2.⁠ ⁠Actual: 30%, Predicted: 29.5%

3.⁠ ⁠Actual: 15.0%, Predicted: 16.2%

4.⁠ ⁠Actual: 40%, Predicted: 38.8%

5.⁠ ⁠Actual: 20%, Predicted: 21.3%

Output- 3