💔 Loss Functions

A Loss Function is a scoreboard that tells the model "How badly did you mess up?"

📉 Mean Squared Error (MSE)

Used for predicting numbers. It takes the model's guess, subtracts the real answer, and squares the difference. It heavily punishes HUGE errors, but ignores tiny ones.

🐍 Python Implementation

from sklearn.metrics import mean_squared_error

true_prices =      [100, 150, 200]
predicted_prices = [105, 140, 205] # Model made some mistakes!

# Calculate MSE
mse = mean_squared_error(true_prices, predicted_prices)
print("Mean Squared Error:", mse)