Fix: broken links found

Author: ajay-dhangar

docs/machine-learning/machine-learning-core/supervised-learning/regression/lasso.mdx

@@ -25,7 +25,7 @@ Where:
 
 ## 2. Feature Selection: The Power of Zero
 
-The most significant difference between Lasso and its sibling, [Ridge Regression](/tutorial/machine-learning/supervised-learning/regression/ridge), is that Lasso can shrink coefficients **exactly to zero**.
+The most significant difference between Lasso and its sibling, [Ridge Regression](./ridge), is that Lasso can shrink coefficients **exactly to zero**.
 
 When a coefficient becomes zero, that feature is effectively removed from the model. This makes Lasso an excellent tool for:
 1.  **Automated Feature Selection:** Identifying the most important variables in a dataset with hundreds of features.