add L3.ipynb

.gitattributes

@@ -1,3 +1,3 @@
 [attr]lfs-file filter=lfs diff=lfs merge=lfs -text
 
-*.pdf lfs-file
+"*.pdf" lfs-file

L2.ipynb

@@ -74,6 +74,7 @@
    "id": "84468a76",
    "metadata": {},
    "source": [
+    "## trace \n",
     "$tr[M] = \\sum^{D}_{i=1}{M_{ii}}$"
    ]
   },

L3.ipynb

@@ -0,0 +1,163 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "70f73980",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e8012b5c",
+   "metadata": {},
+   "source": [
+    "# Numerical Optimization\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bea6fa0f",
+   "metadata": {},
+   "source": [
+    "## Linear Classifier\n",
+    "\n",
+    "$D = \\set{x_i, y_i }^N_{i=1}$ is given. ($x_i \\in \\R^D,\\, y_i\\in \\set{0, 1}$)\n",
+    "\n",
+    "like"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "3ad846b8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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truncated
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "np.random.seed(7)\n",
+    "\n",
+    "y = np.random.randint(0, 2, size=20)\n",
+    "\n",
+    "x = np.random.normal(0, 0.08, size=(2, 20)) + np.vstack([y / 2 + 0.25, y / 2 + 0.25])\n",
+    "\n",
+    "plt.xlim(0, 1)\n",
+    "plt.ylim(0, 1)\n",
+    "\n",
+    "plt.scatter(x[0, :][y == 0], x[1, :][y == 0], color=\"red\", label=\"y = 0\")\n",
+    "plt.scatter(x[0, :][y == 1], x[1, :][y == 1], color=\"blue\", label=\"y = 1\")\n",
+    "\n",
+    "plt.legend()\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8b9e393c",
+   "metadata": {},
+   "source": [
+    "we want to create a **classifier**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8bb1768a",
+   "metadata": {},
+   "source": [
+    "first, set a target function\n",
+    "\n",
+    "$$L(w) = \\frac{1}{2}\\sum_{i}^{N}{| f(x_i; w) - y_i|^2}$$\n",
+    "\n",
+    "then how to get $w^* = \\text{argmin} L(w) $: $w$ to get lowest $L(w)$"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "18da07bf",
+   "metadata": {},
+   "source": [
+    "## Learning (Optimization)\n",
+    "\n",
+    "$$f(x; w) = w^Tx$$\n",
+    "\n",
+    "$$L(w) = \\frac{1}{2}\\sum{|w^Tx_i - y_i|^2} \\\\=\\frac{1}{2} (w^Tx - y)^2\\\\= \\frac{1}{2}{(w^Tx - y)}^T{(w^Tx - y)}$$\n",
+    "\n",
+    "$$\\frac{dL}{dw} = x(x^Tw-y)$$\n",
+    "\n",
+    "in order to minimize $L(w)$, \n",
+    "$$\\left.\\frac{dL}{dw}\\right|_{w=w^*} = 0$$\n",
+    "\n",
+    "therefore,\n",
+    "\n",
+    "$$\\frac{dL}{dw} = $$\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bcb16cc8",
+   "metadata": {},
+   "source": [
+    "Analytic Method\n",
+    "\n",
+    "$$\\frac{dL}{dw} = 0 \\to$$\n",
+    "\n",
+    "Numerical Method\n",
+    "\n",
+    "* gradient descent\n",
+    "\n",
+    "$$w_{t+1} = w_t - \\eta \\left . \\frac{dL}{dw} \\right |_{w=w_t}$$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "71cb6971",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6577fc8a",
+   "metadata": {},
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "2025-02-AI (3.12.11)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

main.py

@@ -1,6 +0,0 @@
-def main():
-    print("Hello from 2025-02-ai!")
-
-
-if __name__ == "__main__":
-    main()

pyproject.toml

@@ -8,4 +8,5 @@ dependencies = [
     "jupyter>=1.1.1",
     "matplotlib>=3.10.6",
     "numpy>=2.3.3",
+    "pymupdf>=1.26.4",
 ]

uv.lock

@@ -14,6 +14,7 @@ dependencies = [
     { name = "jupyter" },
     { name = "matplotlib" },
     { name = "numpy" },
+    { name = "pymupdf" },
 ]
 
 [package.metadata]
@@ -21,6 +22,7 @@ requires-dist = [
     { name = "jupyter", specifier = ">=1.1.1" },
     { name = "matplotlib", specifier = ">=3.10.6" },
     { name = "numpy", specifier = ">=2.3.3" },
+    { name = "pymupdf", specifier = ">=1.26.4" },
 ]
 
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 ]
 
+[[package]]
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+    { url = "https://files.pythonhosted.org/packages/d8/13/0916e8e02cb5453161fb9d9167c747d0a20d58633e30728645374153f815/pymupdf-1.26.4-cp39-abi3-manylinux_2_28_aarch64.whl", hash = "sha256:2604f687dd02b6a1b98c81bd8becfc0024899a2d2085adfe3f9e91607721fd22", size = 23454948, upload-time = "2025-08-25T21:20:07.71Z" },
+    { url = "https://files.pythonhosted.org/packages/4e/c6/d3cfafc75d383603884edeabe4821a549345df954a88d79e6764e2c87601/pymupdf-1.26.4-cp39-abi3-manylinux_2_28_x86_64.whl", hash = "sha256:973a6dda61ebd34040e4df3753bf004b669017663fbbfdaa294d44eceba98de0", size = 24060686, upload-time = "2025-08-25T14:17:56.536Z" },
+    { url = "https://files.pythonhosted.org/packages/72/08/035e9d22c801e801bba50c6745bc90ba8696a042fe2c68793e28bf0c3b07/pymupdf-1.26.4-cp39-abi3-musllinux_1_2_x86_64.whl", hash = "sha256:299a49797df5b558e695647fa791329ba3911cbbb31ed65f24a6266c118ef1a7", size = 24265046, upload-time = "2025-08-25T14:18:21.238Z" },
+    { url = "https://files.pythonhosted.org/packages/28/8c/c201e4846ec0fb6ae5d52aa3a5d66f9355f0c69fb94230265714df0de65e/pymupdf-1.26.4-cp39-abi3-win32.whl", hash = "sha256:51b38379aad8c71bd7a8dd24d93fbe7580c2a5d9d7e1f9cd29ebbba315aa1bd1", size = 17127332, upload-time = "2025-08-25T14:18:39.132Z" },
+    { url = "https://files.pythonhosted.org/packages/d1/c4/87d27b108c2f6d773aa5183c5ae367b2a99296ea4bc16eb79f453c679e30/pymupdf-1.26.4-cp39-abi3-win_amd64.whl", hash = "sha256:0b6345a93a9afd28de2567e433055e873205c52e6b920b129ca50e836a3aeec6", size = 18743491, upload-time = "2025-08-25T14:19:01.104Z" },
+]
+
 [[package]]
 name = "pyparsing"
 version = "3.2.3"