diff --git a/docs/examples/dcn.ipynb b/docs/examples/dcn.ipynb
index 12da7d01..e3125d47 100644
--- a/docs/examples/dcn.ipynb
+++ b/docs/examples/dcn.ipynb
@@ -68,7 +68,7 @@
         "**What are feature crosses and why are they important?** Imagine that we are building a recommender system to sell a blender to customers. Then, a customer's past purchase history such as `purchased_bananas` and `purchased_cooking_books`, or geographic features, are single features. If one has purchased both bananas **and** cooking books, then this customer will more likely click on the recommended blender. The combination of `purchased_bananas` and `purchased_cooking_books` is referred to as a **feature cross**, which provides additional interaction information beyond the individual features.\n",
         "\u003cdiv\u003e\n",
         "\u003ccenter\u003e\n",
-        "\u003cimg src=\"http://drive.google.com/uc?export=view\u0026id=1e8pYZHM1ZSwqBLYVkKDoGg0_2t2UPc2y\" width=\"600\"/\u003e\n",
+        "\u003cimg src=\"https://github.com/tensorflow/recommenders/blob/main/assets/cross_features.gif?raw=true\" width=\"600\"/\u003e\n",
         "\u003c/center\u003e\n",
         "\u003c/div\u003e\n",
         "\n",
@@ -86,7 +86,7 @@
         "polynomial degree increases with layer depth. The following figure shows the $(i+1)$-th cross layer.\n",
         "\u003cdiv class=\"fig figcenter fighighlight\"\u003e\n",
         "\u003ccenter\u003e\n",
-        "  \u003cimg src=\"http://drive.google.com/uc?export=view\u0026id=1QvIDptMxixFNp6P4bBqMN4AYAhAIAYQZ\" width=\"50%\" style=\"display:block\"\u003e\n",
+        "  \u003cimg src=\"https://github.com/tensorflow/recommenders/blob/main/assets/feature_crossing.png?raw=true\" width=\"50%\" style=\"display:block\"\u003e\n",
         "  \u003c/center\u003e\n",
         "\u003c/div\u003e\n",
         "*   Deep Network. It is a traditional feedforward multilayer perceptron (MLP).\n",
@@ -96,8 +96,8 @@
         "\n",
         "\u003cdiv class=\"fig figcenter fighighlight\"\u003e\n",
         "\u003ccenter\u003e\n",
-        "  \u003cimg src=\"http://drive.google.com/uc?export=view\u0026id=1WtDUCV6b-eetUnWVCAmcPh8mJFut5EUd\" hspace=\"40\" width=\"30%\" style=\"margin: 0px 100px 0px 0px;\"\u003e\n",
-        "  \u003cimg src=\"http://drive.google.com/uc?export=view\u0026id=1xo_twKb847hasfss7JxF0UtFX_rEb4nt\" width=\"20%\"\u003e\n",
+        "  \u003cimg src=\"https://github.com/tensorflow/recommenders/blob/main/assets/parallel_deep_cross.png?raw=true\" hspace=\"40\" width=\"30%\" style=\"margin: 0px 100px 0px 0px;\"\u003e\n",
+        "  \u003cimg src=\"https://github.com/tensorflow/recommenders/blob/main/assets/stacked_deep_cross.png?raw=true\" width=\"20%\"\u003e\n",
         "  \u003c/center\u003e\n",
         "\u003c/div\u003e"
       ]
@@ -760,7 +760,7 @@
         "**DCN (stacked).** We first train a DCN model with a stacked structure, that is, the inputs are fed to a cross network followed by a deep network.\n",
         "\u003cdiv\u003e\n",
         "\u003ccenter\u003e\n",
-        "\u003cimg src=\"http://drive.google.com/uc?export=view\u0026id=1X8qoMtIYKJz4yBYifvfw4QpAwrjr70e_\" width=\"140\"/\u003e\n",
+        "\u003cimg src=\"https://github.com/tensorflow/recommenders/blob/main/assets/stacked_structure.png?raw=true\" width=\"140\"/\u003e\n",
         "\u003c/center\u003e\n",
         "\u003c/div\u003e\n"
       ]
@@ -787,7 +787,7 @@
         "\n",
         "\u003cdiv\u003e\n",
         "\u003ccenter\u003e\n",
-        "\u003cimg src=\"http://drive.google.com/uc?export=view\u0026id=1ZZfUTNdxjGAaAuwNrweKkLJ1PGxMmiCm\" width=\"400\"/\u003e\n",
+        "\u003cimg src=\"https://github.com/tensorflow/recommenders/blob/main/assets/low_rank_dcn.png?raw=true\" width=\"400\"/\u003e\n",
         "\u003c/center\u003e\n",
         "\u003c/div\u003e\n"
       ]
@@ -874,7 +874,7 @@
         "\n",
         "\u003cdiv class=\"fig figcenter fighighlight\"\u003e\n",
         "\u003ccenter\u003e\n",
-        "  \u003cimg src=\"http://drive.google.com/uc?export=view\u0026id=11RpNuj9s0OgSav9TUuGA7v7PuFLL6nVR\" hspace=40 width=\"600\" style=\"display:block;\"\u003e\n",
+        "  \u003cimg src=\"https://github.com/tensorflow/recommenders/blob/main/assets/alternate_dcn_structures.png?raw=true\" hspace=40 width=\"600\" style=\"display:block;\"\u003e\n",
         "  \u003cdiv class=\"figcaption\"\u003e\n",
         "  \u003cb\u003eLeft\u003c/b\u003e: DCN with a parallel structure; \u003cb\u003eRight\u003c/b\u003e: Concatenating cross layers. \n",
         "  \u003c/div\u003e\n",