add lecture 13

lectures/00_configuration/installcommands.txt

@@ -3,5 +3,16 @@ pip install scikit-learn
 pip install ultralytics 
 pip install ultralytics opencv-python
 pip install transformers
+pip install ipykernel
 # pip install sentencepiece did not work
-conda install sentencepiece
+conda install sentencepiece
+
+
+For AI Agents
+- Create a different envirofment: python version 3.11
+- installl pytorch
+- pip install browser-use
+- pip install "browser-use[memory]"
+- playwright install chromium --with-deps --no-shell
+
+

lectures/08_multiclass_classification_n_to_n_2hidden/keyconcetps_multiclass_classification.ipynb

@@ -10,7 +10,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 69,
+   "execution_count": 30,
    "id": "2d8b3880",
    "metadata": {},
    "outputs": [
@@ -69,7 +69,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 70,
+   "execution_count": 31,
    "id": "02ff97f3",
    "metadata": {},
    "outputs": [
@@ -134,7 +134,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 71,
+   "execution_count": 32,
    "id": "af64b425",
    "metadata": {},
    "outputs": [
@@ -187,7 +187,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 72,
+   "execution_count": 33,
    "id": "c26b1fa2",
    "metadata": {},
    "outputs": [
@@ -229,7 +229,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 73,
+   "execution_count": 34,
    "id": "8d3cb18e",
    "metadata": {},
    "outputs": [],
@@ -239,7 +239,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 79,
+   "execution_count": 35,
    "id": "7e4a9a78",
    "metadata": {},
    "outputs": [
@@ -281,6 +281,29 @@
     "print(f\"Cross-Entropy Loss (One Example): {loss:.4f}\")"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "d4436c0d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Cross-Entropy Loss (One Example): 0.2191\n"
+     ]
+    }
+   ],
+   "source": [
+    "# corss entroy using torch library\n",
+    "# F.cross_entropy expects: [batch_size, num_classes]\n",
+    "import torch\n",
+    "from torch.nn import functional as F\n",
+    "loss= F.cross_entropy(torch.tensor([logits],  dtype=torch.float32), torch.tensor([one_hot_target],  dtype=torch.float32))\n",
+    "print(f\"Cross-Entropy Loss (One Example): {loss:.4f}\")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "9000b450",
@@ -294,7 +317,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 75,
+   "execution_count": 37,
    "id": "4d146b28",
    "metadata": {},
    "outputs": [