{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": " Линейная_регрессия,_градиентный_спуск.ipynb",
"provenance": [],
"collapsed_sections": []
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"accelerator": "GPU"
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "8S0l1cfKEdcQ"
},
"source": [
"# **План**\n",
"\n",
"- Реализация алгоритма стохастического градиентного спуска:\n",
" - загрузка данных\n",
" - создание и обучение алгоритма\n",
"- Сравнение написанного алгоритма с реализованным в библиотеке Sklearn.\n",
"\n",
"- Рекомендованная литература"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "WBIx7HpJwCKa"
},
"source": [
"ноутбук в колаб: https://drive.google.com/file/d/1aqRvKK0WRq8hn89bm1O__khM5cg1wuW7/view?usp=sharing"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "xvGoXa3CFAeV"
},
"source": [
"# Реализуем алгоритм стохастического градиентного спуска"
]
},
{
"cell_type": "code",
"metadata": {
"id": "8JSYdc4UJD6s"
},
"source": [
"import numpy as np\n",
"\n",
"import pandas as pd\n",
"import matplotlib.pyplot as plt"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "markdown",
"metadata": {
"id": "4oW8ZZWAXN2E"
},
"source": [
"## Загрузка и подготовка данных\n",
"\n",
"### **Постановка задачи:** \n",
"Предсказать вероятность одобрения заявки на поступление в ВУЗ (вероятность от 0 до 1) по набору признаков: оценки за экзамены, наличие research и тд"
]
},
{
"cell_type": "code",
"metadata": {
"id": "vW1tcon9JTEQ"
},
"source": [
"df = pd.read_csv('https://raw.githubusercontent.com/tixonsit/mmdad_materials/master/datasets_14872_228180_Admission_Predict_Ver1.1.csv')\n",
"del df['Serial No.']"
],
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"metadata": {
"id": "oUQRj1lsJlFR",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 204
},
"outputId": "f39b113b-4be6-4892-ac0b-6ee50245296b"
},
"source": [
"df.head()"
],
"execution_count": null,
"outputs": [
{
"output_type": "execute_result",
"data": {
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