Merge pull request #123 from woodnx:kotsugi

knock67まで

kotsugi/chapter07/knock60.ipynb

@@ -0,0 +1,144 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "from dotenv import load_dotenv\n",
+    "load_dotenv()\n",
+    "\n",
+    "FILE_DIR = os.getenv('FILE_DIR')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from gensim.models import KeyedVectors\n",
+    "\n",
+    "model = KeyedVectors.load_word2vec_format(f\"{FILE_DIR}/GoogleNews-vectors-negative300.bin\", binary=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([-3.61328125e-02, -4.83398438e-02,  2.35351562e-01,  1.74804688e-01,\n",
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+       "       -1.97265625e-01, -1.12792969e-01,  1.29882812e-01,  1.96289062e-01,\n",
+       "        1.56402588e-03,  3.93066406e-02,  2.17773438e-01, -1.43554688e-01,\n",
+       "        6.03027344e-02, -1.35742188e-01,  1.16210938e-01, -1.59912109e-02,\n",
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+       "       -1.65039062e-01, -2.46093750e-01, -2.35595703e-02, -2.11914062e-01,\n",
+       "        1.84570312e-01, -1.85546875e-02,  2.16796875e-01,  5.05371094e-02,\n",
+       "        2.02636719e-02,  4.25781250e-01,  1.28906250e-01, -2.77099609e-02,\n",
+       "        1.29882812e-01, -1.15722656e-01, -2.05078125e-02,  1.49414062e-01,\n",
+       "        7.81250000e-03, -2.05078125e-01, -8.05664062e-02, -2.67578125e-01,\n",
+       "       -2.29492188e-02, -8.20312500e-02,  8.64257812e-02,  7.61718750e-02,\n",
+       "       -3.66210938e-02,  5.22460938e-02, -1.22070312e-01, -1.44042969e-02,\n",
+       "       -2.69531250e-01,  8.44726562e-02, -2.52685547e-02, -2.96630859e-02,\n",
+       "       -1.68945312e-01,  1.93359375e-01, -1.08398438e-01,  1.94091797e-02,\n",
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+       "       -1.01562500e-01, -1.31835938e-01,  7.51953125e-02, -7.66601562e-02,\n",
+       "        3.37219238e-03, -8.59375000e-02,  1.25000000e-01,  2.92968750e-02,\n",
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+       "        2.11914062e-01, -4.44335938e-02,  6.12792969e-02,  2.62451172e-02,\n",
+       "       -1.77734375e-01,  1.23046875e-01, -7.42187500e-02, -1.67968750e-01,\n",
+       "       -1.08886719e-01, -9.04083252e-04, -7.37304688e-02,  5.49316406e-02,\n",
+       "        6.03027344e-02,  8.39843750e-02,  9.17968750e-02, -1.32812500e-01,\n",
+       "        1.22070312e-01, -8.78906250e-03,  1.19140625e-01, -1.94335938e-01,\n",
+       "       -6.64062500e-02, -2.07031250e-01,  7.37304688e-02,  8.93554688e-02,\n",
+       "        1.81884766e-02, -1.20605469e-01, -2.61230469e-02,  2.67333984e-02,\n",
+       "        7.76367188e-02, -8.30078125e-02,  6.78710938e-02, -3.54003906e-02,\n",
+       "        3.10546875e-01, -2.42919922e-02, -1.41601562e-01, -2.08007812e-01,\n",
+       "       -4.57763672e-03, -6.54296875e-02, -4.95605469e-02,  2.22656250e-01,\n",
+       "        1.53320312e-01, -1.38671875e-01, -5.24902344e-02,  4.24804688e-02,\n",
+       "       -2.38281250e-01,  1.56250000e-01,  5.83648682e-04, -1.20605469e-01,\n",
+       "       -9.22851562e-02, -4.44335938e-02,  3.61328125e-02, -1.86767578e-02,\n",
+       "       -8.25195312e-02, -8.25195312e-02, -4.05273438e-02,  1.19018555e-02,\n",
+       "        1.69921875e-01, -2.80761719e-02,  3.03649902e-03,  9.32617188e-02,\n",
+       "       -8.49609375e-02,  1.57470703e-02,  7.03125000e-02,  1.62353516e-02,\n",
+       "       -2.27050781e-02,  3.51562500e-02,  2.47070312e-01, -2.67333984e-02],\n",
+       "      dtype=float32)"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model.get_vector(\"United_States\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "venv",
+   "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": "3.12.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

kotsugi/chapter07/knock61.ipynb

@@ -0,0 +1,57 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from importnb import imports\n",
+    "\n",
+    "with imports(\"ipynb\"):\n",
+    "  from knock60 import model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.7310774"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model.similarity(\"United_States\", \"U.S.\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "venv",
+   "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": "3.12.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

kotsugi/chapter07/knock62.ipynb

@@ -0,0 +1,80 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from importnb import imports\n",
+    "\n",
+    "with imports(\"ipynb\"):\n",
+    "  from knock60 import model"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "`model.most_similar`関数で，第一引数の単語とコサイン類似度が高い10語を出力"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "result = model.most_similar(\"United_States\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "01: Unites_States      0.7877249121665955\n",
+      "02: Untied_States      0.7541369795799255\n",
+      "03: United_Sates       0.7400726079940796\n",
+      "04: U.S.               0.7310774326324463\n",
+      "05: theUnited_States   0.6404393315315247\n",
+      "06: America            0.6178411841392517\n",
+      "07: UnitedStates       0.6167312860488892\n",
+      "08: Europe             0.6132988333702087\n",
+      "09: countries          0.6044804453849792\n",
+      "10: Canada             0.6019068956375122\n"
+     ]
+    }
+   ],
+   "source": [
+    "for i, item in enumerate(result):\n",
+    "  print(f\"{i+1:02}: {item[0].ljust(18)} {item[1]}\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "venv",
+   "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": "3.12.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

kotsugi/chapter07/knock63.ipynb

@@ -0,0 +1,73 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from importnb import imports\n",
+    "\n",
+    "with imports(\"ipynb\"):\n",
+    "  from knock60 import model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "result = model.most_similar(positive=[\"Spain\", \"Athens\"], negative=[\"Madrid\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "01: Greece                    0.6898481845855713\n",
+      "02: Aristeidis_Grigoriadis    0.560684859752655\n",
+      "03: Ioannis_Drymonakos        0.5552908778190613\n",
+      "04: Greeks                    0.5450685620307922\n",
+      "05: Ioannis_Christou          0.5400861501693726\n",
+      "06: Hrysopiyi_Devetzi         0.5248444676399231\n",
+      "07: Heraklio                  0.5207760334014893\n",
+      "08: Athens_Greece             0.5168810486793518\n",
+      "09: Lithuania                 0.5166866183280945\n",
+      "10: Iraklion                  0.5146791934967041\n"
+     ]
+    }
+   ],
+   "source": [
+    "for i, item in enumerate(result):\n",
+    "  print(f\"{i+1:02}: {item[0].ljust(25)} {item[1]}\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "venv",
+   "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": "3.12.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}