upd

1 files changed, 15 insertions, 5 deletions

diff --git a/Fundamentals_of_Accelerated_Data_Science/2-04_networkx_cugraph.ipynb b/Fundamentals_of_Accelerated_Data_Science/2-04_networkx_cugraph.ipynb
index dee3520..48764b4 100644
--- a/Fundamentals_of_Accelerated_Data_Science/2-04_networkx_cugraph.ipynb
+++ b/Fundamentals_of_Accelerated_Data_Science/2-04_networkx_cugraph.ipynb
@@ -226,12 +226,15 @@
    "metadata": {},
    "source": [
     "### Betweenness Centrality ###\n",
-    "Quantifies the number of times a node acts as a bridge along the shortest path between two other nodes, highlighting its importance in information flow"
+    "Quantifies the number of times a node acts as a bridge along the shortest path between two other nodes, highlighting its importance in information flow\n",
+    "\n",
+    "For every pair of vertices in a connected graph, there exists at least one shortest path between the vertices, that is, there exists at least one path such that either the number of edges that the path passes through (for unweighted graphs) or the sum of the weights of the edges (for weighted graphs) is minimized.\n",
+    "\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "id": "281374af-c7cf-4592-a34d-796c1158dab6",
    "metadata": {},
    "outputs": [],
@@ -264,7 +267,10 @@
    "metadata": {},
    "source": [
     "### Katz Centrality ###\n",
-    "Measures a node's centrality based on its global influence in the network, considering both direct and indirect connections"
+    "Measures a node's centrality based on its global influence in the network, considering both direct and indirect connections\n",
+    "\n",
+    "\n",
+    "Katz centrality measures influence by taking into account the total number of walks between a pair of actors"
    ]
   },
   {
@@ -283,7 +289,9 @@
    "metadata": {},
    "source": [
     "### Pagerank Centrality ###\n",
-    "Determines a node's importance based on the quantity and quality of links to it, similar to Google's original PageRank algorithm"
+    "Determines a node's importance based on the quantity and quality of links to it, similar to Google's original PageRank algorithm\n",
+    "\n",
+    "PageRank’s main difference from EigenCentrality is that it accounts for link direction. Each node in a network is assigned a score based on its number of incoming links (its ‘indegree’). These links are also weighted depending on the relative score of its originating node."
    ]
   },
   {
@@ -302,7 +310,9 @@
    "metadata": {},
    "source": [
     "### Eigenvector Centrality ###\n",
-    "Assigns scores to nodes based on the principle that connections to high-scoring nodes contribute more to the node's own score than connections to low-scoring nodes"
+    "Assigns scores to nodes based on the principle that connections to high-scoring nodes contribute more to the node's own score than connections to low-scoring nodes\n",
+    "\n",
+    "connections to high-scoring nodes contribute more to the score of the node in question than equal connections to low-scoring nodes. A high eigenvector score means that a node is connected to many nodes who themselves have high scores."
    ]
   },
   {