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  "cells": [
    {
      "id": "d4cec5b7-5725-44d3-bfb7-04278fdf9bb4",
      "cell_type": "code",
      "source": "import pandas as pd\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.preprocessing import StandardScaler, LabelEncoder\nfrom sklearn.neural_network import MLPClassifier\nfrom sklearn.metrics import accuracy_score, confusion_matrix",
      "metadata": {
        "trusted": true
      },
      "outputs": [],
      "execution_count": 2
    },
    {
      "id": "0e3d0d27-300b-4152-96e0-70ff1fbab83a",
      "cell_type": "code",
      "source": "data = pd.read_csv(\"Churn_Modelling.csv\")",
      "metadata": {
        "trusted": true
      },
      "outputs": [],
      "execution_count": 3
    },
    {
      "id": "06fd9a81-ed4d-4796-bc38-e0c68fe1dc3e",
      "cell_type": "code",
      "source": "X = data.iloc[:, 3:13]   # Features from CreditScore to EstimatedSalary\ny = data.iloc[:, 13] ",
      "metadata": {
        "trusted": true
      },
      "outputs": [],
      "execution_count": 4
    },
    {
      "id": "90c9c5aa-0b8a-424b-a625-ff4fc2d73380",
      "cell_type": "code",
      "source": "le = LabelEncoder()\nX[\"Gender\"] = le.fit_transform(X[\"Gender\"])\nX = pd.get_dummies(X, columns=[\"Geography\"], drop_first=True)",
      "metadata": {
        "trusted": true
      },
      "outputs": [],
      "execution_count": 5
    },
    {
      "id": "4b0ecfe6-7245-4866-a842-e422c5658928",
      "cell_type": "code",
      "source": "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)",
      "metadata": {
        "trusted": true
      },
      "outputs": [],
      "execution_count": 6
    },
    {
      "id": "55cd9306-83f0-4ea6-8399-278444f3e839",
      "cell_type": "code",
      "source": "scaler = StandardScaler()\nX_train = scaler.fit_transform(X_train)\nX_test = scaler.transform(X_test)",
      "metadata": {
        "trusted": true
      },
      "outputs": [],
      "execution_count": 7
    },
    {
      "id": "60cdf8fb-c656-4a24-a120-de0c4c9abf94",
      "cell_type": "code",
      "source": "",
      "metadata": {
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      "outputs": [],
      "execution_count": null
    }
  ]
}