Fix: broken links err

Author: ajay-dhangar

docs/machine-learning/machine-learning-core/supervised-learning/classification/random-forest.mdx

@@ -5,7 +5,7 @@ description: "Understanding Ensemble Learning, Bagging, and how Random Forests r
 tags: [machine-learning, supervised-learning, classification, ensemble-learning, random-forest]
 ---
 
-A **Random Forest** is an **Ensemble Learning** method that operates by constructing a multitude of [Decision Trees](/tutorial/machine-learning/supervised-learning/classification/decision-trees) during training. For classification tasks, the output of the random forest is the class selected by most trees (majority voting).
+A **Random Forest** is an **Ensemble Learning** method that operates by constructing a multitude of [Decision Trees](../decision-trees) during training. For classification tasks, the output of the random forest is the class selected by most trees (majority voting).
 
 The fundamental philosophy of Random Forest is that **a group of "weak learners" can come together to form a "strong learner."**