[pre-commit.ci] auto fixes from pre-commit.com hooks

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machine_learning/ridge_regression/model.py

@@ -1,18 +1,18 @@
 import numpy as np
 import pandas as pd
 
 
 class RidgeRegression:
     def __init__(self, alpha:float=0.001, regularization_param:float=0.1, num_iterations:int=1000) -> None:
         self.alpha:float = alpha
         self.regularization_param:float = regularization_param
         self.num_iterations:int = num_iterations
         self.theta:np.ndarray = None
 
 <<<<<<< HEAD
 
     def feature_scaling(self, X:np.ndarray) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
 =======
     def feature_scaling(self, X):
 >>>>>>> d4fc2bf852ec4a023380f4ef367edefa88fd6881
         mean = np.mean(X, axis=0)
@@ -45,7 +45,7 @@
 
 <<<<<<< HEAD
     def compute_cost(self, X:np.ndarray, y:np.ndarray) -> float:
-        X_scaled, _, _ = self.feature_scaling(X)  
+        X_scaled, _, _ = self.feature_scaling(X)
 =======
     def compute_cost(self, X, y):
         X_scaled, _, _ = self.feature_scaling(X)
@@ -71,7 +71,7 @@
 
 <<<<<<< HEAD
     # added bias term to the feature matrix
-    X = np.c_[np.ones(X.shape[0]), X] 
+    X = np.c_[np.ones(X.shape[0]), X]
 =======
     # Add bias term (intercept) to the feature matrix
     X = np.c_[np.ones(X.shape[0]), X]