diff --git a/open-machine-learning-jupyter-book/_toc.yml b/open-machine-learning-jupyter-book/_toc.yml
index e1842461f..478f83569 100644
--- a/open-machine-learning-jupyter-book/_toc.yml
+++ b/open-machine-learning-jupyter-book/_toc.yml
@@ -213,6 +213,7 @@ parts:
     - file: assignments/deep-learning/cnn/how-to-choose-cnn-architecture-mnist
     - file: assignments/deep-learning/cnn/sign-language-digits-classification-with-cnn
     - file: assignments/deep-learning/cnn/object-recognition-in-images-using-cnn
+    - file: assignments/deep-learning/cnn/image-classification
     - file: assignments/deep-learning/tensorflow/intro_to_tensorflow_for_deeplearning
     - file: assignments/deep-learning/lstm/bitcoin-lstm-model-with-tweet-volume-and-sentiment
     - file: assignments/deep-learning/rnn/google-stock-price-prediction-rnn
@@ -225,6 +226,7 @@ parts:
     - file: assignments/deep-learning/dqn/dqn-on-foreign-exchange-market
     - file: assignments/deep-learning/gan/art-by-gan
     - file: assignments/deep-learning/gan/gan-introduction
+    - file: assignments/deep-learning/image-segmentation/comparing-edge-based-and-region-based-segmentation
     - file: assignments/deep-learning/difussion-model/denoising-difussion-model
     - file: assignments/deep-learning/object-detection/car-object-detection
     - file: assignments/deep-learning/overview/basic-classification-classify-images-of-clothing
diff --git a/open-machine-learning-jupyter-book/deep-learning/image-classification.ipynb b/open-machine-learning-jupyter-book/deep-learning/image-classification.ipynb
index 56f4d51c5..2486078d3 100644
--- a/open-machine-learning-jupyter-book/deep-learning/image-classification.ipynb
+++ b/open-machine-learning-jupyter-book/deep-learning/image-classification.ipynb
@@ -219,8 +219,8 @@
    "source": [
     "- Using small 3×3 filters to replace large convolutional kernels.\n",
     "- After replacing the convolution kernel, the convolution layers have the same perceptual field. \n",
-    "- Each layer is trained by Re LU activation function and batch gradient descent after convolution operation.\n",
-    "- It is verified that increasing the network depth can improve the model performance Although, VGG has achieved good results in image classification and localization problems in 2014 due to its deeper network structure and low computational complexity, it uses 140 million parameters and is computationally intensive, which is its shortcoming."
+    "- Each layer is trained by ReLU activation function and batch gradient descent after convolution operation.\n",
+    "- It is verified that increasing the network depth can improve the model performance. Although, VGG has achieved good results in image classification and localization problems in 2014 due to its deeper network structure and low computational complexity, it uses 140 million parameters and is computationally intensive, which is its shortcoming."
    ]
   },
   {
@@ -1156,7 +1156,7 @@
    "id": "b4552758",
    "metadata": {},
    "source": [
-    "TBD."
+    "Assignment - [Image classification](../../assignments/deep-learning/cnn/image-classification.ipynb)"
    ]
   },
   {
diff --git a/open-machine-learning-jupyter-book/deep-learning/image-segmentation.ipynb b/open-machine-learning-jupyter-book/deep-learning/image-segmentation.ipynb
index 7c2d3556d..abbe6c89a 100644
--- a/open-machine-learning-jupyter-book/deep-learning/image-segmentation.ipynb
+++ b/open-machine-learning-jupyter-book/deep-learning/image-segmentation.ipynb
@@ -2045,7 +2045,7 @@
    "id": "a0994ed1",
    "metadata": {},
    "source": [
-    "TBD."
+    "Assignment - [Comparing edge-based and region-based segmentation](../../assignments/deep-learning/image-segmentation/comparing-edge-based-and-region-based-segmentation.ipynb)"
    ]
   },
   {
diff --git a/open-machine-learning-jupyter-book/deep-learning/lstm.ipynb b/open-machine-learning-jupyter-book/deep-learning/lstm.ipynb
index c920b28b0..6ea5b6e8f 100644
--- a/open-machine-learning-jupyter-book/deep-learning/lstm.ipynb
+++ b/open-machine-learning-jupyter-book/deep-learning/lstm.ipynb
@@ -4770,7 +4770,7 @@
    "source": [
     "## Your turn! 🚀\n",
     "\n",
-    "Practice the Long-Short Term Memory Networks by following this TBD.\n",
+    "Assignment - [Bitcoin lstm model with tweet volume and sentiment](../../assignments/deep-learning/lstm/bitcoin-lstm-model-with-tweet-volume-and-sentiment.ipynb)\n",
     "\n",
     "## Acknowledgments\n",
     "\n",