From b056ca1b90a25e2f3db98627bbd18f99483e4166 Mon Sep 17 00:00:00 2001
From: Harsh Upadhyay <142519913+Harshupadhyay221@users.noreply.github.com>
Date: Thu, 6 Jun 2024 15:35:17 +0530
Subject: [PATCH] Update Simple+Linear+Regression+in+Python.ipynb

---
 .../Simple+Linear+Regression+in+Python.ipynb                    | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/Simple Linear Regression in Python/Simple+Linear+Regression+in+Python.ipynb b/Simple Linear Regression in Python/Simple+Linear+Regression+in+Python.ipynb
index 5bef2ac..12fc303 100644
--- a/Simple Linear Regression in Python/Simple+Linear+Regression+in+Python.ipynb	
+++ b/Simple Linear Regression in Python/Simple+Linear+Regression+in+Python.ipynb	
@@ -1310,7 +1310,7 @@
     "\n",
     "<br>\n",
     "\n",
-    "You should be able to answer this by now!\n",
+    "A "good" RMSE depends on the specific application, data scale, and business requirements. Always compare your model's RMSE against baselines, competitors, and domain-specific benchmarks to determine its adequacy. Aim for an RMSE that balances predictive accuracy with the practical needs and goals of your project.\n",
     "\n",
     "\n",
     "<br>\n",