From db5837d83ddb70d7bb8da1a09a24861b132cafb0 Mon Sep 17 00:00:00 2001
From: Aditya <109960864+KondeAditya@users.noreply.github.com>
Date: Thu, 6 Nov 2025 18:08:40 +0530
Subject: [PATCH] Delete 3_bank_customer.ipynb

---
 3_bank_customer.ipynb | 95 -------------------------------------------
 1 file changed, 95 deletions(-)
 delete mode 100644 3_bank_customer.ipynb

diff --git a/3_bank_customer.ipynb b/3_bank_customer.ipynb
deleted file mode 100644
index 5740a5b..0000000
--- a/3_bank_customer.ipynb
+++ /dev/null
@@ -1,95 +0,0 @@
-{
-  "metadata": {
-    "kernelspec": {
-      "name": "python",
-      "display_name": "Python (Pyodide)",
-      "language": "python"
-    },
-    "language_info": {
-      "codemirror_mode": {
-        "name": "python",
-        "version": 3
-      },
-      "file_extension": ".py",
-      "mimetype": "text/x-python",
-      "name": "python",
-      "nbconvert_exporter": "python",
-      "pygments_lexer": "ipython3",
-      "version": "3.8"
-    }
-  },
-  "nbformat_minor": 5,
-  "nbformat": 4,
-  "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": {
-        "trusted": true
-      },
-      "outputs": [],
-      "execution_count": null
-    }
-  ]
-}
\ No newline at end of file