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"cells": [
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"cell_type": "markdown",
"source": [
"# Tuần 1 - Setup & Data EDA trên Google Colab\n",
"## Bước 1: Setup Google Colab Notebook"
],
"metadata": {
"id": "u9z9FB4FYxX6"
}
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"id": "1qcMefdGYp44"
},
"outputs": [],
"source": [
"!pip install transformers datasets pandas numpy matplotlib seaborn plotly scikit-learn -q"
]
},
{
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"source": [
"## Bước 2: Import Libraries"
],
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}
},
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"cell_type": "code",
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import seaborn as sns\n",
"import plotly.express as px\n",
"import plotly.graph_objects as go\n",
"import sklearn.model_selection as train_test_split\n",
"from sklearn.preprocessing import LabelEncoder\n",
"import warnings\n",
"warnings.filterwarnings('ignore')\n",
"print(\"✅ All libraries imported successfully!\")"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "K0w99VbrZLQz",
"outputId": "0d0f8ebd-9169-4906-aa12-5262ab10e574"
},
"execution_count": 4,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"✅ All libraries imported successfully!\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"## Bước 3: Load Dataset"
],
"metadata": {
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}
},
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"source": [
"# Load Dataset từ HuggingFace\n",
"from datasets import load_dataset\n",
"\n",
"# Load IMDB dataset (50,000 reviews thực tế)\n",
"dataset = load_dataset('imdb')\n",
"\n",
"# Convert sang pandas DataFrame\n",
"train_df = pd.DataFrame(dataset['train'])\n",
"test_df = pd.DataFrame(dataset['test'])\n",
"\n",
"print(f\"✅ Train set: {len(train_df):,} rows\")\n",
"print(f\"✅ Test set: {len(test_df):,} rows\")\n",
"print(f\"\\n📋 Columns: {train_df.columns.tolist()}\")\n",
"print(f\"\\n🔍 Sample data:\")"
],
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"text": [
"Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads.\n",
"WARNING:huggingface_hub.utils._http:Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads.\n"
]
},
{
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"data": {
"text/plain": [
"plain_text/train-00000-of-00001.parquet: 0%| | 0.00/21.0M [00:00\n",
"\n",
"\n",
" \n",
"\n",
"