Update interview_prep.md

Author: Amogh Singhal

interview_prep.md

@@ -46,7 +46,7 @@ Target mean encoding
 | K-nearest neighbors     | Classification         | - Accuracy - Precision - Recall - F-beta score - Area under ROC curve                                                                                                | - Low Bias High Variance                | Sensitive to outliers                   | Sensitive to imbalanced data                           |   |
 | Decision Tree           | Both                   | Both                                                                                                | - Low Bias High Variance                 | - Not impacted by outliers                   | - Not impacted by imbalanced data                           |   |
 | Random Forest           | Both                   | Both                                                                                                | - Low Bias High Variance                 | - Not impacted by outliers                   | - Not impacted by imbalanced data                          |   |
-| K-means clustering      | Clustering             | - Elbow method - Silhoutte Analysis                                                                                                 |               |                    |                           |   |
+| K-means clustering      | Clustering             | - Elbow method - Silhoutte Analysis                                                                                                 |               | Senstive to Outliers                   |                           |   |
 |                         |                        |                                                                                                 |               |                    |                           |   |
 
 ### 22. Why do CNNs perfom better with images ? (What is it that CNN achieve better than ANN when delaing with image data)