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

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

@@ -210,8 +210,8 @@
     "language_code": "pa"
   },
   "4-Classification/3-Classifiers-2/solution/notebook.ipynb": {
-    "original_hash": "70f41fe4fd4253adb44cd9d291406e4f",
-    "translation_date": "2026-02-28T10:39:57+00:00",
+    "original_hash": "382c1f542f31fcc58137ce6d14751413",
+    "translation_date": "2026-04-24T11:06:07+00:00",
     "source_file": "4-Classification/3-Classifiers-2/solution/notebook.ipynb",
     "language_code": "pa"
   },

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

@@ -7,46 +7,23 @@
    "cell_type": "markdown",
    "metadata": {}
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### ਡੇਟਾਸੈਟ ਝਲਕ\n",
+    "ਇਸ ਡੇਟਾਸੈਟ ਵਿੱਚ ਵਿਅਕਤੀਗਤ ਨਮੂਨੇ (ਉਦਾਹਰਣ ਵਜੋਂ, ਵਿਅੰਜਨ) ਸ਼ਾਮਲ ਹਨ ਜੋ ਖਾਣ-ਪੀਣ ਦੀ ਕਿਸਮ ਦੇ ਨਾਲ ਲੇਬਲ ਕੀਤੇ ਗਏ ਹਨ।  \n",
+    "ਹਰ ਕਤਾਰ ਇੱਕ ਇਕੱਲੇ ਨਮੂਨੇ/ਰਿਕਾਰਡ ਦੇ ਬਰਾਬਰ ਹੁੰਦੀ ਹੈ, ਅਤੇ ਕਾਲਮ ਵਰਗੀਕਰਨ ਲਈ ਵਰਤੇ ਜਾਣ ਵਾਲੇ ਸਮੱਗਰੀਆਂ ਜਾਂ ਹੋਰ ਲੱਛਣਾਂ ਨੂੰ ਦਰਸਾਉਂਦੇ ਹਨ, ਜਿਸ ਵਿੱਚ `cuisine` ਲੇਬਲ ਸ਼ਾਮਲ ਹੈ।\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": [
-    "# ਵੱਖ-ਵੱਖ ਕਲਾਸੀਫਾਇਰਾਂ ਨੂੰ ਕੋਸ਼ਿਸ਼ ਕਰੋ\n"
+    "# ਵੱਖ-ਵੱਖ ਕਲਾਸੀਫਾਇਰ ਆਜ਼ਮਾਓ\n"
    ]
   },
   {
@@ -263,7 +240,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "---\n\n<!-- CO-OP TRANSLATOR DISCLAIMER START -->\n**ਅਸਵੀਕਾਰੋਪੱਤਰ**:  \nਇਹ ਦਸਤਾਵੇਜ਼ ਏਆਈ ਅਨੁਵਾਦ ਸੇਵਾ [Co-op Translator](https://github.com/Azure/co-op-translator) ਦੀ ਵਰਤੋਂ ਕਰਕੇ ਅਨੁਵਾਦ ਕੀਤਾ ਗਿਆ ਹੈ। ਜਦੋਂ ਕਿ ਅਸੀਂ ਸ਼ੁੱਧਤਾ ਲਈ ਕੋਸ਼ਿਸ਼ ਕਰਦੇ ਹਾਂ, ਕਿਰਪਾ ਕਰਕੇ ਧਿਆਨ ਵਿੱਚ ਰੱਖੋ ਕਿ ਸਵੈਚਾਲਿਤ ਅਨੁਵਾਦਾਂ ਵਿੱਚ ਗਲਤੀਆਂ ਜਾਂ ਅਸਥਿਰਤਾ ਹੋ ਸਕਦੀ ਹੈ। ਮੂਲ ਦਸਤਾਵੇਜ਼ ਆਪਣੀ ਮੂਲ ਭਾਸ਼ਾ ਵਿੱਚ ਹੀ ਅਥਾਰਟੀਟਿਵ ਸੰਦਰਭ ਮੰਨਿਆ ਜਾਣਾ ਚਾਹੀਦਾ ਹੈ। ਜ਼ਰੂਰੀ ਜਾਣਕਾਰੀ ਲਈ, ਨਿਪੁੰਨ ਮਨੁੱਖੀ ਅਨੁਵਾਦ ਸਿਫਾਰਸ਼ੀ ਹੈ। ਇਸ ਅਨੁਵਾਦ ਦੀ ਵਰਤੋਂ ਤੋਂ पैदा ਹੋਣ ਵਾਲੀਆਂ ਕਿਸੇ ਵੀ ਗਲਤਫਹਿਮੀਆਂ ਜਾਂ ਗਲਤ ਵਿਆਖਿਆਵਾਂ ਲਈ ਅਸੀਂ ਜ਼ਿੰਮੇਵਾਰ ਨਹੀਂ ਹਾਂ।\n<!-- CO-OP TRANSLATOR DISCLAIMER END -->\n"
+    "---\n\n<!-- CO-OP TRANSLATOR DISCLAIMER START -->\n**ਡਿਸਕਲੇਮਰ**:  \nਇਹ ਦਸਤਾਵੇਜ਼ ਏਆਈ ਅਨੁਵਾਦ ਸੇਵਾ [Co-op Translator](https://github.com/Azure/co-op-translator) ਦੀ ਵਰਤੋਂ ਨਾਲ ਅਨੁਵਾਦਿਤ ਕੀਤਾ ਗਿਆ ਹੈ। ਜਦੋਂ ਕਿ ਅਸੀਂ ਸਹੀਅਤਾ ਲਈ ਕੋਸ਼ਿਸ਼ ਕਰਦੇ ਹਾਂ, ਕਿਰਪਾ ਕਰਕੇ ਧਿਆਨ ਵਿੱਚ ਰੱਖੋ ਕਿ ਆਟੋਮੇਟਿਕ ਅਨੁਵਾਦਾਂ ਵਿੱਚ ਗਲਤੀਆਂ ਜਾਂ ਅਣਸਹੀ ਯਤਾਦ ਹੋ ਸਕਦੀਆਂ ਹਨ। ਮੂਲ ਦਸਤਾਵੇਜ਼ ਆਪਣੀ ਮੂਲ ਭਾਸ਼ਾ ਵਿੱਚ ਹੀ ਅਧਿਕਾਰਿਤ ਸਰੋਤ ਮੰਨਿਆ ਜਾਣਾ ਚਾਹੀਦਾ ਹੈ। ਮਹੱਤਵਪੂਰਨ ਜਾਣਕਾਰੀ ਲਈ, ਪ੍ਰੋਫੈਸ਼ਨਲ ਮਨੁੱਖੀ ਅਨੁਵਾਦ ਦੀ ਸਿਫਾਰਿਸ਼ ਕੀਤੀ ਜਾਂਦੀ ਹੈ। ਇਸ ਅਨੁਵਾਦ ਦੀ ਵਰਤੋਂ ਤੋਂ ਉਤਪੰਨ ਕਿਸੇ ਵੀ ਗਲਤਫ਼ਹਮੀ ਜਾਂ ਭ੍ਰਮ ਲਈ ਅਸੀਂ ਜ਼ਿੰਮੇਵਾਰ ਨਹੀਂ ਹਾਂ।\n<!-- CO-OP TRANSLATOR DISCLAIMER END -->\n"
    ]
   }
  ],

translations/pt-BR/.co-op-translator.json

@@ -210,8 +210,8 @@
     "language_code": "pt-BR"
   },
   "4-Classification/3-Classifiers-2/solution/notebook.ipynb": {
-    "original_hash": "70f41fe4fd4253adb44cd9d291406e4f",
-    "translation_date": "2026-02-28T10:40:18+00:00",
+    "original_hash": "382c1f542f31fcc58137ce6d14751413",
+    "translation_date": "2026-04-24T11:06:26+00:00",
     "source_file": "4-Classification/3-Classifiers-2/solution/notebook.ipynb",
     "language_code": "pt-BR"
   },

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

@@ -2,51 +2,28 @@
  "cells": [
   {
    "source": [
-    "# Construa Mais Modelos de Classificação\n"
+    "# Construir Mais Modelos de Classificação\n"
    ],
    "cell_type": "markdown",
    "metadata": {}
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Visão geral do conjunto de dados\n",
+    "Este conjunto de dados contém amostras individuais (por exemplo, receitas) rotuladas por culinária.\n",
+    "Cada linha corresponde a uma única amostra/registro, e as colunas representam ingredientes ou outros atributos usados para classificação, incluindo o rótulo `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**Aviso Legal**:  \nEste documento foi traduzido utilizando o serviço de tradução por IA [Co-op Translator](https://github.com/Azure/co-op-translator). Embora nos empenhemos para garantir a precisão, esteja ciente de que traduções automáticas podem conter erros ou imprecisões. O documento original em seu idioma nativo deve ser considerado a fonte autorizada. Para informações críticas, recomenda-se tradução profissional realizada por humanos. Não nos responsabilizamos por quaisquer mal-entendidos ou interpretações incorretas decorrentes do uso desta tradução.\n<!-- CO-OP TRANSLATOR DISCLAIMER END -->\n"
+    "---\n\n<!-- CO-OP TRANSLATOR DISCLAIMER START -->\n**Aviso Legal**:  \nEste documento foi traduzido usando o serviço de tradução AI [Co-op Translator](https://github.com/Azure/co-op-translator). Embora nos esforcemos pela precisão, por favor, esteja ciente de que traduções automáticas podem conter erros ou imprecisões. O documento original em seu idioma nativo deve ser considerado a fonte autorizada. Para informações críticas, recomenda-se tradução profissional humana. Não nos responsabilizamos por quaisquer mal-entendidos ou interpretações equivocadas decorrentes do uso desta tradução.\n<!-- CO-OP TRANSLATOR DISCLAIMER END -->\n"
    ]
   }
  ],

translations/pt-PT/.co-op-translator.json

@@ -210,8 +210,8 @@
     "language_code": "pt-PT"
   },
   "4-Classification/3-Classifiers-2/solution/notebook.ipynb": {
-    "original_hash": "70f41fe4fd4253adb44cd9d291406e4f",
-    "translation_date": "2026-02-28T10:40:08+00:00",
+    "original_hash": "382c1f542f31fcc58137ce6d14751413",
+    "translation_date": "2026-04-24T11:06:16+00:00",
     "source_file": "4-Classification/3-Classifiers-2/solution/notebook.ipynb",
     "language_code": "pt-PT"
   },

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

@@ -7,46 +7,23 @@
    "cell_type": "markdown",
    "metadata": {}
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Visão Geral do Conjunto de Dados\n",
+    "Este conjunto de dados contém amostras individuais (por exemplo, receitas) rotuladas por cozinha.\n",
+    "Cada linha corresponde a uma única amostra/registo, e as colunas representam ingredientes ou outros atributos usados para classificação, incluindo o rótulo `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()"
    ]
@@ -124,7 +101,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Experimente diferentes classificadores\n"
+    "# Experimente classificadores diferentes\n"
    ]
   },
   {
@@ -263,7 +240,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "---\n\n<!-- CO-OP TRANSLATOR DISCLAIMER START -->\n**Aviso Legal**:\nEste documento foi traduzido utilizando o serviço de tradução automática [Co-op Translator](https://github.com/Azure/co-op-translator). Embora nos esforcemos para garantir a precisão, por favor tenha em conta que traduções automáticas podem conter erros ou imprecisões. O documento original na sua língua nativa deve ser considerado a fonte autorizada. Para informações críticas, recomenda-se a tradução profissional realizada por um ser humano. Não nos responsabilizamos por quaisquer mal-entendidos ou interpretações incorretas decorrentes da utilização desta tradução.\n<!-- CO-OP TRANSLATOR DISCLAIMER END -->\n"
+    "---\n\n<!-- CO-OP TRANSLATOR DISCLAIMER START -->\n**Aviso Legal**:  \nEste documento foi traduzido utilizando o serviço de tradução por IA [Co-op Translator](https://github.com/Azure/co-op-translator). Embora nos esforcemos por garantir a precisão, esteja ciente de que traduções automáticas podem conter erros ou imprecisões. O documento original na sua língua nativa deve ser considerado a fonte autoritativa. Para informações críticas, recomenda-se a tradução profissional humana. Não nos responsabilizamos por quaisquer mal-entendidos ou interpretações erradas decorrentes da utilização desta tradução.\n<!-- CO-OP TRANSLATOR DISCLAIMER END -->\n"
    ]
   }
  ],