Example code

Example.ipynb

@@ -0,0 +1,173 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Using TensorFlow backend.\n"
+     ]
+    }
+   ],
+   "source": [
+    "import gensim\n",
+    "\n",
+    "# Load pre-trained Word2Vec model.\n",
+    "model = gensim.models.KeyedVectors.load('data/pl.bin')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[('królowa', 0.6799831390380859),\n",
+       " ('cesarzowa', 0.6074954867362976),\n",
+       " ('księżniczka', 0.5475618839263916),\n",
+       " ('księżna', 0.5279887318611145),\n",
+       " ('waza', 0.5248866081237793),\n",
+       " ('konstancja', 0.5197093486785889),\n",
+       " ('królową', 0.5182099938392639),\n",
+       " ('dama', 0.5130698084831238),\n",
+       " ('elżbieta', 0.5102220773696899),\n",
+       " ('króla', 0.5050344467163086)]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model.most_similar(positive=['kobieta', 'król'], negative=['mężczyzna'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[('królowa', 0.9603520631790161),\n",
+       " ('cesarzowa', 0.9171873331069946),\n",
+       " ('księżniczka', 0.8568219542503357),\n",
+       " ('elżbieta', 0.8513852953910828),\n",
+       " ('księżna', 0.8503665924072266),\n",
+       " ('konstancja', 0.8395503759384155),\n",
+       " ('inkwizycja', 0.834706723690033),\n",
+       " ('dynastia', 0.8325018882751465),\n",
+       " ('królową', 0.828750491142273),\n",
+       " ('izabela', 0.8216117024421692)]"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model.most_similar_cosmul(positive=['kobieta', 'król'], negative=['mężczyzna'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[('wyjść', 0.8666046261787415),\n",
+       " ('ruszyć', 0.8621427416801453),\n",
+       " ('wylądować', 0.856998860836029),\n",
+       " ('zejść', 0.856095552444458),\n",
+       " ('zamieszkać', 0.8547601699829102),\n",
+       " ('wyruszyć', 0.8522873520851135),\n",
+       " ('przejść', 0.846845805644989),\n",
+       " ('uderzyć', 0.846382200717926),\n",
+       " ('zaatakować', 0.8440034985542297),\n",
+       " ('stanąć', 0.8418554663658142)]"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "model.most_similar_cosmul(positive=['otworzyć', 'wejść'], negative=['włączyć'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "%matplotlib inline\n",
+    "%config InlineBackend.figure_format = 'retina'\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "from sklearn.manifold import TSNE\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# viz_words = 500\n",
+    "# tsne = TSNE()\n",
+    "# embed_tsne = tsne.fit_transform(embed_mat[:viz_words, :])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "# fig, ax = plt.subplots(figsize=(14, 14))\n",
+    "# for idx in range(viz_words):\n",
+    "#     plt.scatter(*embed_tsne[idx, :], color='steelblue')\n",
+    "#     plt.annotate(int_to_vocab[idx], (embed_tsne[idx, 0], embed_tsne[idx, 1]), alpha=0.7)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python [conda env:py3]",
+   "language": "python",
+   "name": "conda-env-py3-py"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.6.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}