diff --git a/P1. Baseline.ipynb b/P1. Baseline.ipynb
index 793ceb5..9fbe285 100644
--- a/P1. Baseline.ipynb	
+++ b/P1. Baseline.ipynb	
@@ -1053,15 +1053,21 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": 21,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "# Implement recommender system which will recommend movies (which user hasn't seen) which is similar to BaselineUI\n",
-    "# but first subtract column means then row means\n",
-    "# The output should be saved in 'Recommendations generated/ml-100k/Self_BaselineIU_reco.csv'\n",
-    "# and 'Recommendations generated/ml-100k/Self_BaselineIU_estimations.csv'"
+    "Implement recommender system which will recommend movies (which user hasn't seen) which is similar to BaselineUI but first subtract column means then row means.\n",
+    "\n",
+    "The output should be saved in 'Recommendations generated/ml-100k/Self_BaselineIU_reco.csv' and 'Recommendations generated/ml-100k/Self_BaselineIU_estimations.csv'.\n",
+    "\n",
+    "<br><br>\n",
+    "Additional clarification: \n",
+    "\n",
+    "Summarizing, the prediction of the rating of the user u regarding the item i should be equal to b_u + b_i.\n",
+    "The procedure to get b_u and b_i is the following:\n",
+    "- We have the original user-item ratings matrix M.\n",
+    "- For each column representing the item i, we compute the mean of ratings and denote by b_i. From each rating in matrix M we subtract the corresponding column mean (b_i) to receive new matrix M'.\n",
+    "- For each row of matrix M' representing the user u, we compute the mean of ratings and denote by b_u."
    ]
   },
   {