Add files via upload

2025-10-30 23:08:07 +05:30
commit d0bbee40e2
7 changed files with 1757 additions and 0 deletions
@@ -0,0 +1,95 @@
+{
+  "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
+    }
+  ]
+}