Added documentation links

notebooks/notebooks.yml

@@ -272,4 +272,15 @@ units:
           - name: "In-class demo, part 2"
             file: "Lesson_29_demo_part2.ipynb"
           - name: "Activity part 2"
-            file: "Lesson_29_activity_part2.ipynb"
+            file: "Lesson_29_activity_part2.ipynb"
+          - name: "Activity part 2 solution"
+            file: "Lesson_29_activity_part2_solution.ipynb"
+
+      - number: "31"
+        title: "Convolutional Neural Networks"
+        topics: "Convolutional and pooling layers, CNN architectures"
+        notebooks:
+          - name: "In-class demo"
+            file: "Lesson_31_demo.ipynb"
+          - name: "Activity"
+            file: "Lesson_31_activity.ipynb"

notebooks/unit4/lesson_29/Lesson_29_demo_part2.ipynb

@@ -9,6 +9,9 @@
     "\n",
     "In this notebook, we build a deep neural network (DNN) classifier for the CIFAR-10 dataset using PyTorch's `nn.Sequential` module. The CIFAR-10 dataset consists of 60,000 32x32 color images in 10 classes. We convert the images to grayscale (single channel) and use only fully connected layers (no convolution or pooling) to demonstrate the fundamentals of deep learning classification.\n",
     "\n",
+    "- **Dataset**: [CIFAR-10](https://www.cs.toronto.edu/~kriz/cifar.html)\n",
+    "- **PyTorch documentation**: [`torchvision.datasets.CFAR10()`](https://docs.pytorch.org/vision/main/generated/torchvision.datasets.CIFAR10.html)\n",
+    "\n",
     "## Notebook set-up\n",
     "\n",
     "### Imports"