For my final project I used food macronutrient and micronutrient information to predict that calories that a certain food item will be. Preproecssing was done on the dataset and EDA was created. Machine learning models used were linear reegression, random forests, and K-Nearest-Neighbors on continuos variable. Then we split calories into groups using thresholds defined and ran a random forest and a neural network testing for accuracy.
Highest accuracy: Neural Network at 97%
Items Attatched:
-Python code for music genre detection
-Presentation on results and key findings from project
-Biliography of the dataset used on Kaggle