chore(i18n): sync translations with latest source changes (chunk 1/1, 6 changes)

translations/hi/.co-op-translator.json

@@ -210,8 +210,8 @@
     "language_code": "hi"
   },
   "4-Classification/3-Classifiers-2/solution/notebook.ipynb": {
-    "original_hash": "70f41fe4fd4253adb44cd9d291406e4f",
-    "translation_date": "2026-02-28T10:05:49+00:00",
+    "original_hash": "382c1f542f31fcc58137ce6d14751413",
+    "translation_date": "2026-04-24T11:02:01+00:00",
     "source_file": "4-Classification/3-Classifiers-2/solution/notebook.ipynb",
     "language_code": "hi"
   },

translations/hi/4-Classification/3-Classifiers-2/solution/notebook.ipynb

@@ -7,46 +7,23 @@
    "cell_type": "markdown",
    "metadata": {}
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Dataset Overview\n",
+    "यह डेटासेट व्यक्तिगत नमूनों (उदाहरण के लिए, रेसिपी) को भोजन शैली के अनुसार लेबल करता है।\n",
+    "प्रत्येक पंक्ति एक एकल नमूना/रिकॉर्ड के लिए होती है, और कॉलम वर्गीकरण के लिए उपयोग किए जाने वाले सामग्री या अन्य गुणों का प्रतिनिधित्व करते हैं, जिसमें `cuisine` लेबल भी शामिल है।\n"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {},
-   "outputs": [
-    {
-     "output_type": "execute_result",
-     "data": {
-      "text/plain": [
-       "   Unnamed: 0 cuisine  almond  angelica  anise  anise_seed  apple  \\\n",
-       "0           0  indian       0         0      0           0      0   \n",
-       "1           1  indian       1         0      0           0      0   \n",
-       "2           2  indian       0         0      0           0      0   \n",
-       "3           3  indian       0         0      0           0      0   \n",
-       "4           4  indian       0         0      0           0      0   \n",
-       "\n",
-       "   apple_brandy  apricot  armagnac  ...  whiskey  white_bread  white_wine  \\\n",
-       "0             0        0         0  ...        0            0           0   \n",
-       "1             0        0         0  ...        0            0           0   \n",
-       "2             0        0         0  ...        0            0           0   \n",
-       "3             0        0         0  ...        0            0           0   \n",
-       "4             0        0         0  ...        0            0           0   \n",
-       "\n",
-       "   whole_grain_wheat_flour  wine  wood  yam  yeast  yogurt  zucchini  \n",
-       "0                        0     0     0    0      0       0         0  \n",
-       "1                        0     0     0    0      0       0         0  \n",
-       "2                        0     0     0    0      0       0         0  \n",
-       "3                        0     0     0    0      0       0         0  \n",
-       "4                        0     0     0    0      0       1         0  \n",
-       "\n",
-       "[5 rows x 382 columns]"
-      ],
-      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Unnamed: 0</th>\n      <th>cuisine</th>\n      <th>almond</th>\n      <th>angelica</th>\n      <th>anise</th>\n      <th>anise_seed</th>\n      <th>apple</th>\n      <th>apple_brandy</th>\n      <th>apricot</th>\n      <th>armagnac</th>\n      <th>...</th>\n      <th>whiskey</th>\n      <th>white_bread</th>\n      <th>white_wine</th>\n      <th>whole_grain_wheat_flour</th>\n      <th>wine</th>\n      <th>wood</th>\n      <th>yam</th>\n      <th>yeast</th>\n      <th>yogurt</th>\n      <th>zucchini</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0</td>\n      <td>indian</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1</td>\n      <td>indian</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2</td>\n      <td>indian</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>3</td>\n      <td>indian</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>4</td>\n      <td>indian</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 382 columns</p>\n</div>"
-     },
-     "metadata": {},
-     "execution_count": 1
-    }
-   ],
+   "outputs": [],
    "source": [
     "import pandas as pd\n",
+    "# Load dataset containing cuisine features\n",
     "cuisines_df = pd.read_csv(\"../../data/cleaned_cuisines.csv\")\n",
     "cuisines_df.head()"
    ]
@@ -124,7 +101,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# विभिन्न वर्गीकर्ताओं को आज़माएं\n"
+    "# विभिन्न वर्गीकर्ताओं को आजमाएं\n"
    ]
   },
   {
@@ -263,7 +240,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "---\n\n<!-- CO-OP TRANSLATOR DISCLAIMER START -->\n**अस्वीकरण**:\nइस दस्तावेज़ का अनुवाद AI अनुवाद सेवा [Co-op Translator](https://github.com/Azure/co-op-translator) का उपयोग करके किया गया है। हम सटीकता के लिए प्रयासरत हैं, लेकिन कृपया ध्यान दें कि स्वचालित अनुवादों में त्रुटियाँ या अशुद्धताएँ हो सकती हैं। मूल दस्तावेज़ अपनी मातृभाषा में आधिकारिक स्रोत माना जाना चाहिए। महत्वपूर्ण जानकारी के लिए, पेशेवर मानव अनुवाद की सलाह दी जाती है। इस अनुवाद के उपयोग से उत्पन्न किसी भी गलतफहमी या गलत व्याख्या के लिए हम जिम्मेदार नहीं हैं।\n<!-- CO-OP TRANSLATOR DISCLAIMER END -->\n"
+    "---\n\n<!-- CO-OP TRANSLATOR DISCLAIMER START -->\n**अस्वीकरण**:  \nइस दस्तावेज़ का अनुवाद एआई अनुवाद सेवा [Co-op Translator](https://github.com/Azure/co-op-translator) का उपयोग करके किया गया है। जबकि हम सटीकता के लिए प्रयासरत हैं, कृपया ध्यान दें कि स्वचालित अनुवाद में त्रुटियाँ या अशुद्धियाँ हो सकती हैं। मूल दस्तावेज़ को उसकी मूल भाषा में ही अधिकारिक स्रोत माना जाना चाहिए। महत्वपूर्ण जानकारी के लिए, पेशेवर मानव अनुवाद की सिफारिश की जाती है। इस अनुवाद के उपयोग से उत्पन्न किसी भी गलतफहमी या गलत व्याख्या के लिए हम जिम्मेदार नहीं हैं।\n<!-- CO-OP TRANSLATOR DISCLAIMER END -->\n"
    ]
   }
  ],

translations/ja/.co-op-translator.json

@@ -210,8 +210,8 @@
     "language_code": "ja"
   },
   "4-Classification/3-Classifiers-2/solution/notebook.ipynb": {
-    "original_hash": "70f41fe4fd4253adb44cd9d291406e4f",
-    "translation_date": "2026-02-28T10:05:29+00:00",
+    "original_hash": "382c1f542f31fcc58137ce6d14751413",
+    "translation_date": "2026-04-24T11:01:42+00:00",
     "source_file": "4-Classification/3-Classifiers-2/solution/notebook.ipynb",
     "language_code": "ja"
   },

translations/ja/4-Classification/3-Classifiers-2/solution/notebook.ipynb

@@ -7,46 +7,23 @@
    "cell_type": "markdown",
    "metadata": {}
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### データセットの概要\n",
+    "このデータセットには、料理の種類でラベル付けされた個々のサンプル（例：レシピ）が含まれています。  \n",
+    "各行は単一のサンプル／レコードに対応し、列は分類に使用される材料やその他の属性、`cuisine`ラベルを表しています。\n"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {},
-   "outputs": [
-    {
-     "output_type": "execute_result",
-     "data": {
-      "text/plain": [
-       "   Unnamed: 0 cuisine  almond  angelica  anise  anise_seed  apple  \\\n",
-       "0           0  indian       0         0      0           0      0   \n",
-       "1           1  indian       1         0      0           0      0   \n",
-       "2           2  indian       0         0      0           0      0   \n",
-       "3           3  indian       0         0      0           0      0   \n",
-       "4           4  indian       0         0      0           0      0   \n",
-       "\n",
-       "   apple_brandy  apricot  armagnac  ...  whiskey  white_bread  white_wine  \\\n",
-       "0             0        0         0  ...        0            0           0   \n",
-       "1             0        0         0  ...        0            0           0   \n",
-       "2             0        0         0  ...        0            0           0   \n",
-       "3             0        0         0  ...        0            0           0   \n",
-       "4             0        0         0  ...        0            0           0   \n",
-       "\n",
-       "   whole_grain_wheat_flour  wine  wood  yam  yeast  yogurt  zucchini  \n",
-       "0                        0     0     0    0      0       0         0  \n",
-       "1                        0     0     0    0      0       0         0  \n",
-       "2                        0     0     0    0      0       0         0  \n",
-       "3                        0     0     0    0      0       0         0  \n",
-       "4                        0     0     0    0      0       1         0  \n",
-       "\n",
-       "[5 rows x 382 columns]"
-      ],
-      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Unnamed: 0</th>\n      <th>cuisine</th>\n      <th>almond</th>\n      <th>angelica</th>\n      <th>anise</th>\n      <th>anise_seed</th>\n      <th>apple</th>\n      <th>apple_brandy</th>\n      <th>apricot</th>\n      <th>armagnac</th>\n      <th>...</th>\n      <th>whiskey</th>\n      <th>white_bread</th>\n      <th>white_wine</th>\n      <th>whole_grain_wheat_flour</th>\n      <th>wine</th>\n      <th>wood</th>\n      <th>yam</th>\n      <th>yeast</th>\n      <th>yogurt</th>\n      <th>zucchini</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0</td>\n      <td>indian</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1</td>\n      <td>indian</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2</td>\n      <td>indian</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>3</td>\n      <td>indian</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>4</td>\n      <td>indian</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 382 columns</p>\n</div>"
-     },
-     "metadata": {},
-     "execution_count": 1
-    }
-   ],
+   "outputs": [],
    "source": [
     "import pandas as pd\n",
+    "# Load dataset containing cuisine features\n",
     "cuisines_df = pd.read_csv(\"../../data/cleaned_cuisines.csv\")\n",
     "cuisines_df.head()"
    ]
@@ -124,7 +101,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# 異なる分類器を試す\n"
+    "# さまざまな分類器を試す\n"
    ]
   },
   {
@@ -263,7 +240,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "---\n\n<!-- CO-OP TRANSLATOR DISCLAIMER START -->\n**免責事項**：  \n本書類はAI翻訳サービス「Co-op Translator」（https://github.com/Azure/co-op-translator）を使用して翻訳されています。正確性の向上に努めておりますが、自動翻訳には誤りや不正確な部分が含まれる場合があります。原文の言語によるオリジナル文書が権威ある情報源としてご確認ください。重要な情報については、専門の人間による翻訳を推奨します。本翻訳の利用により生じたいかなる誤解や誤訳についても、当方は責任を負いかねます。\n<!-- CO-OP TRANSLATOR DISCLAIMER END -->\n"
+    "---\n\n<!-- CO-OP TRANSLATOR DISCLAIMER START -->\n**免責事項**:  \n本書類はAI翻訳サービス [Co-op Translator](https://github.com/Azure/co-op-translator) を使用して翻訳されています。正確性を期していますが、自動翻訳には誤りや不正確さが含まれる可能性があります。原文のネイティブ言語版が正式な情報源として扱われるべきです。重要な情報については、専門の人間による翻訳を推奨します。本翻訳の利用に起因する誤解や誤訳について、一切の責任を負いかねます。\n<!-- CO-OP TRANSLATOR DISCLAIMER END -->\n"
    ]
   }
  ],

translations/ko/.co-op-translator.json

@@ -210,8 +210,8 @@
     "language_code": "ko"
   },
   "4-Classification/3-Classifiers-2/solution/notebook.ipynb": {
-    "original_hash": "70f41fe4fd4253adb44cd9d291406e4f",
-    "translation_date": "2026-02-28T10:05:39+00:00",
+    "original_hash": "382c1f542f31fcc58137ce6d14751413",
+    "translation_date": "2026-04-24T11:01:51+00:00",
     "source_file": "4-Classification/3-Classifiers-2/solution/notebook.ipynb",
     "language_code": "ko"
   },

translations/ko/4-Classification/3-Classifiers-2/solution/notebook.ipynb

@@ -2,51 +2,28 @@
  "cells": [
   {
    "source": [
-    "# 더 많은 분류 모델 구축\n"
+    "# 더 많은 분류 모델 만들기\n"
    ],
    "cell_type": "markdown",
    "metadata": {}
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 데이터셋 개요\n",
+    "이 데이터셋은 요리별로 라벨이 지정된 개별 샘플(예: 레시피)을 포함합니다.\n",
+    "각 행은 단일 샘플/기록에 해당하며, 열은 분류에 사용되는 재료 또는 기타 속성(예: `cuisine` 라벨)을 나타냅니다.\n"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {},
-   "outputs": [
-    {
-     "output_type": "execute_result",
-     "data": {
-      "text/plain": [
-       "   Unnamed: 0 cuisine  almond  angelica  anise  anise_seed  apple  \\\n",
-       "0           0  indian       0         0      0           0      0   \n",
-       "1           1  indian       1         0      0           0      0   \n",
-       "2           2  indian       0         0      0           0      0   \n",
-       "3           3  indian       0         0      0           0      0   \n",
-       "4           4  indian       0         0      0           0      0   \n",
-       "\n",
-       "   apple_brandy  apricot  armagnac  ...  whiskey  white_bread  white_wine  \\\n",
-       "0             0        0         0  ...        0            0           0   \n",
-       "1             0        0         0  ...        0            0           0   \n",
-       "2             0        0         0  ...        0            0           0   \n",
-       "3             0        0         0  ...        0            0           0   \n",
-       "4             0        0         0  ...        0            0           0   \n",
-       "\n",
-       "   whole_grain_wheat_flour  wine  wood  yam  yeast  yogurt  zucchini  \n",
-       "0                        0     0     0    0      0       0         0  \n",
-       "1                        0     0     0    0      0       0         0  \n",
-       "2                        0     0     0    0      0       0         0  \n",
-       "3                        0     0     0    0      0       0         0  \n",
-       "4                        0     0     0    0      0       1         0  \n",
-       "\n",
-       "[5 rows x 382 columns]"
-      ],
-      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>Unnamed: 0</th>\n      <th>cuisine</th>\n      <th>almond</th>\n      <th>angelica</th>\n      <th>anise</th>\n      <th>anise_seed</th>\n      <th>apple</th>\n      <th>apple_brandy</th>\n      <th>apricot</th>\n      <th>armagnac</th>\n      <th>...</th>\n      <th>whiskey</th>\n      <th>white_bread</th>\n      <th>white_wine</th>\n      <th>whole_grain_wheat_flour</th>\n      <th>wine</th>\n      <th>wood</th>\n      <th>yam</th>\n      <th>yeast</th>\n      <th>yogurt</th>\n      <th>zucchini</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0</td>\n      <td>indian</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>1</td>\n      <td>indian</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2</td>\n      <td>indian</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>3</td>\n      <td>indian</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>4</td>\n      <td>indian</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n    </tr>\n  </tbody>\n</table>\n<p>5 rows × 382 columns</p>\n</div>"
-     },
-     "metadata": {},
-     "execution_count": 1
-    }
-   ],
+   "outputs": [],
    "source": [
     "import pandas as pd\n",
+    "# Load dataset containing cuisine features\n",
     "cuisines_df = pd.read_csv(\"../../data/cleaned_cuisines.csv\")\n",
     "cuisines_df.head()"
    ]
@@ -124,7 +101,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# 다양한 분류기 시도하기\n"
+    "# 다른 분류기 시도하기\n"
    ]
   },
   {
@@ -263,7 +240,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "---\n\n<!-- CO-OP TRANSLATOR DISCLAIMER START -->\n**면책 조항**:  \n본 문서는 AI 번역 서비스 [Co-op Translator](https://github.com/Azure/co-op-translator)를 사용하여 번역되었습니다. 정확성을 위해 노력하고 있으나, 자동 번역에는 오류나 부정확한 내용이 포함될 수 있음을 유의해 주시기 바랍니다. 원본 문서의 원어 버전을 권위 있는 출처로 간주해야 합니다. 중요한 정보의 경우 전문적인 인간 번역을 권장합니다. 본 번역의 사용으로 인한 오해나 잘못된 해석에 대해 당사는 책임을 지지 않습니다.\n<!-- CO-OP TRANSLATOR DISCLAIMER END -->\n"
+    "---\n\n<!-- CO-OP TRANSLATOR DISCLAIMER START -->\n**면책 조항**:  \n이 문서는 AI 번역 서비스 [Co-op Translator](https://github.com/Azure/co-op-translator)를 사용하여 번역되었습니다. 정확성을 위해 노력하고 있지만, 자동 번역에는 오류나 부정확한 내용이 포함될 수 있음을 유의하시기 바랍니다. 원본 문서는 해당 언어의 원문이 권위 있는 출처로 간주되어야 합니다. 중요한 정보의 경우, 전문적인 인간 번역을 권장합니다. 본 번역의 사용으로 인해 발생하는 모든 오해나 잘못된 해석에 대해 당사는 책임을 지지 않습니다.\n<!-- CO-OP TRANSLATOR DISCLAIMER END -->\n"
    ]
   }
  ],