less verbosity

main.py

@@ -1,4 +1,4 @@
-import pandas as pd
+# import pandas as pd
 from data_loader import load_weather_data
 from preprocessing import scale_data, create_sequences, inverse_scale
 from model_train import (
@@ -47,11 +47,6 @@ residuals = y_test - predictions
 errors = abs(residuals)
 
 plot_predictions(date_test, y_test_rescaled, predictions_rescaled)
-print("date_test shape:", date_test.shape)
-print("residuals shape:", residuals.shape)
-print(date_test[:5])
-print(date_test[-5:])
-
 plot_residuals(date_test.to_numpy(), residuals)
 plot_error_hist(errors)
 plot_scatter(y_test.reshape(-1, 1), predictions.reshape(-1, 1))

model_train.py

@@ -23,7 +23,7 @@ def train_linear_regression_gd(X_train, y_train, lr=0.01, n_epochs=1000):
         loss = np.mean(errors ** 2)
         losses.append(loss)
 
-        if epoch % 500 == 0:
+        if epoch % 1000 == 0:
             print(f"Epoch {epoch}: Loss = {loss:.6f}")
 
     print(f"Final Loss: {losses[-1]:.6f}")