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

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

@@ -210,8 +210,8 @@
     "language_code": "fa"
   },
   "4-Classification/3-Classifiers-2/solution/notebook.ipynb": {
-    "original_hash": "70f41fe4fd4253adb44cd9d291406e4f",
-    "translation_date": "2026-02-28T08:34:09+00:00",
+    "original_hash": "382c1f542f31fcc58137ce6d14751413",
+    "translation_date": "2026-04-24T11:47:25+00:00",
     "source_file": "4-Classification/3-Classifiers-2/solution/notebook.ipynb",
     "language_code": "fa"
   },

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

@@ -7,46 +7,23 @@
    "cell_type": "markdown",
    "metadata": {}
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### مرور کلی مجموعه داده\n",
+    "این مجموعه داده شامل نمونه‌های فردی (برای مثال دستورهای آشپزی) با برچسب نوع غذا است.\n",
+    "هر سطر مربوط به یک نمونه/رکورد واحد است و ستون‌ها نمایانگر مواد تشکیل‌دهنده یا سایر ویژگی‌هایی هستند که برای طبقه‌بندی استفاده می‌شوند، از جمله برچسب `cuisine`.\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()"
    ]
@@ -263,7 +240,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "---\n\n<!-- CO-OP TRANSLATOR DISCLAIMER START -->\n**توضیح مهم**:  \nاین سند با استفاده از سرویس ترجمه هوش مصنوعی [Co-op Translator](https://github.com/Azure/co-op-translator) ترجمه شده است. در حالی که ما در پی دقت هستیم، لطفاً توجه داشته باشید که ترجمه‌های خودکار ممکن است حاوی اشتباهات یا نواقص باشند. سند اصلی به زبان بومی آن منبع مرجع و معتبر تلقی می‌شود. برای اطلاعات حیاتی، استفاده از ترجمه حرفه‌ای انسانی توصیه می‌شود. مسئولیتی در قبال سوءتفاهم‌ها یا تفسیرهای نادرست ناشی از استفاده از این ترجمه پذیرفته نمی‌شود.\n<!-- CO-OP TRANSLATOR DISCLAIMER END -->\n"
+    "---\n\n<!-- CO-OP TRANSLATOR DISCLAIMER START -->\n**سلب مسئولیت**:  \nاین سند با استفاده از سرویس ترجمه هوش مصنوعی [Co-op Translator](https://github.com/Azure/co-op-translator) ترجمه شده است. در حالی که ما تلاش می‌کنیم دقت را حفظ کنیم، لطفاً آگاه باشید که ترجمه‌های خودکار ممکن است حاوی اشتباهات یا نادرستی‌هایی باشد. سند اصلی به زبان اصلی خود باید به عنوان منبع معتبر در نظر گرفته شود. برای اطلاعات حیاتی، توصیه می‌شود از ترجمه حرفه‌ای انسانی استفاده شود. ما مسئول هیچ گونه سوءتفاهم یا تفسیر نادرستی که از استفاده این ترجمه ناشی شود، نیستیم.\n<!-- CO-OP TRANSLATOR DISCLAIMER END -->\n"
    ]
   }
  ],

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

@@ -210,8 +210,8 @@
     "language_code": "ur"
   },
   "4-Classification/3-Classifiers-2/solution/notebook.ipynb": {
-    "original_hash": "70f41fe4fd4253adb44cd9d291406e4f",
-    "translation_date": "2026-02-28T08:34:19+00:00",
+    "original_hash": "382c1f542f31fcc58137ce6d14751413",
+    "translation_date": "2026-04-24T11:47:35+00:00",
     "source_file": "4-Classification/3-Classifiers-2/solution/notebook.ipynb",
     "language_code": "ur"
   },

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

@@ -2,51 +2,28 @@
  "cells": [
   {
    "source": [
-    "# مزید درجہ بندی کے ماڈلز بنائیں\n"
+    "# مزید درجہ بندی ماڈلز بنائیں\n"
    ],
    "cell_type": "markdown",
    "metadata": {}
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### جائزہ ڈیٹا سیٹ\n",
+    "اس ڈیٹا سیٹ میں انفرادی نمونے (مثلاً، ترکیبیں) شامل ہیں جنہیں کھانے کے انداز کی بنیاد پر لیبل لگا دیا گیا ہے۔\n",
+    "ہر صف ایک واحد نمونہ/ریکارڈ کی نمائندگی کرتی ہے، اور کالم اجزاء یا دیگر خصوصیات کو ظاہر کرتے ہیں جو درجہ بندی کے لیے استعمال ہوتے ہیں، بشمول `cuisine` لیبل۔\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": [
-    "# مختلف درجہ بند کرنے والے آزما کر دیکھیں\n"
+    "# مختلف درجہ بند کرنے والوں کو آزمائیں\n"
    ]
   },
   {
@@ -263,7 +240,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "---\n\n<!-- CO-OP TRANSLATOR DISCLAIMER START -->\n**ذمہ داری سے معذرت**:\nیہ دستاویز AI ترجمہ سروس [Co-op Translator](https://github.com/Azure/co-op-translator) کا استعمال کرتے ہوئے ترجمہ کی گئی ہے۔ اگرچہ ہم درستگی کے لیے کوشاں ہیں، براہ کرم آگاہ رہیں کہ خودکار ترجموں میں غلطیاں یا عدم وضاحت ہو سکتی ہے۔ اصل دستاویز اپنی مادری زبان میں معتبر ماخذ سمجھی جانی چاہیے۔ اہم معلومات کے لیے پیشہ ور انسانی ترجمہ کی سفارش کی جاتی ہے۔ ہم اس ترجمے کے استعمال سے پیدا ہونے والی کسی بھی غلط فہمی یا غلط تشریح کے ذمہ دار نہیں ہیں۔\n<!-- CO-OP TRANSLATOR DISCLAIMER END -->\n"
+    "---\n\n<!-- CO-OP TRANSLATOR DISCLAIMER START -->\n**ڈس کلیمر**:  \nیہ دستاویز AI ترجمہ سروس [Co-op Translator](https://github.com/Azure/co-op-translator) کا استعمال کرتے ہوئے ترجمہ کی گئی ہے۔ اگرچہ ہم درستگی کے لیے کوشاں ہیں، براہ کرم آگاہ رہیں کہ خودکار تراجم میں غلطیاں یا عدم درستگیاں ہو سکتی ہیں۔ اصل دستاویز اپنی مادری زبان میں معتبر ماخذ سمجھی جانی چاہیے۔ اہم معلومات کے لیے پیشہ ور انسانی ترجمہ کی سفارش کی جاتی ہے۔ اس ترجمے کے استعمال سے پیدا ہونے والی کسی بھی غلط فہمی یا غلط تشریح کی ذمہ داری ہم پر عائد نہیں ہوتی۔\n<!-- CO-OP TRANSLATOR DISCLAIMER END -->\n"
    ]
   }
  ],

translations/zh-CN/.co-op-translator.json

@@ -210,8 +210,8 @@
     "language_code": "zh-CN"
   },
   "4-Classification/3-Classifiers-2/solution/notebook.ipynb": {
-    "original_hash": "70f41fe4fd4253adb44cd9d291406e4f",
-    "translation_date": "2026-02-28T08:34:30+00:00",
+    "original_hash": "382c1f542f31fcc58137ce6d14751413",
+    "translation_date": "2026-04-24T11:47:44+00:00",
     "source_file": "4-Classification/3-Classifiers-2/solution/notebook.ipynb",
     "language_code": "zh-CN"
   },

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

@@ -7,46 +7,23 @@
    "cell_type": "markdown",
    "metadata": {}
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 数据集概览\n",
+    "此数据集包含按菜系标记的单个样本（例如食谱）。\n",
+    "每行对应一个单独的样本/记录，列表示用于分类的成分或其他属性，包括 `cuisine` 标签。\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()"
    ]
@@ -263,7 +240,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "---\n\n<!-- CO-OP TRANSLATOR DISCLAIMER START -->\n**免责声明**：\n本文档通过 AI 翻译服务 [Co-op Translator](https://github.com/Azure/co-op-translator) 进行了翻译。虽然我们力求准确，但请注意自动翻译可能包含错误或不准确之处。请以原始语言的原始文档为权威来源。对于重要内容，建议采用专业人工翻译。我们不对因使用本翻译而产生的任何误解或误释承担责任。\n<!-- CO-OP TRANSLATOR DISCLAIMER END -->\n"
+    "---\n\n<!-- CO-OP TRANSLATOR DISCLAIMER START -->\n**免责声明**：  \n本文件使用 AI 翻译服务 [Co-op Translator](https://github.com/Azure/co-op-translator) 进行翻译。虽然我们力求准确，但请注意自动翻译可能包含错误或不准确之处。原始语言的原文应被视为权威来源。对于关键信息，建议采用专业人工翻译。我们对因使用本翻译而产生的任何误解或误读不承担责任。\n<!-- CO-OP TRANSLATOR DISCLAIMER END -->\n"
    ]
   }
  ],