From ecee428b6c6b50b0a680636c1237fcc51ad7121e Mon Sep 17 00:00:00 2001
From: benjas <909336740@qq.com>
Date: Sat, 23 Jan 2021 12:12:21 +0800
Subject: [PATCH] Add. JData Project introduction

---
 .../数据清洗-checkpoint.ipynb             |   6 +
 .../数据清洗.ipynb                        | 129 ++++++++++++++++++
 2 files changed, 135 insertions(+)
 create mode 100644 机器学习竞赛实战_优胜解决方案/京东用户购买意向预测/.ipynb_checkpoints/数据清洗-checkpoint.ipynb
 create mode 100644 机器学习竞赛实战_优胜解决方案/京东用户购买意向预测/数据清洗.ipynb

diff --git a/机器学习竞赛实战_优胜解决方案/京东用户购买意向预测/.ipynb_checkpoints/数据清洗-checkpoint.ipynb b/机器学习竞赛实战_优胜解决方案/京东用户购买意向预测/.ipynb_checkpoints/数据清洗-checkpoint.ipynb
new file mode 100644
index 0000000..2fd6442
--- /dev/null
+++ b/机器学习竞赛实战_优胜解决方案/京东用户购买意向预测/.ipynb_checkpoints/数据清洗-checkpoint.ipynb
@@ -0,0 +1,6 @@
+{
+ "cells": [],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/机器学习竞赛实战_优胜解决方案/京东用户购买意向预测/数据清洗.ipynb b/机器学习竞赛实战_优胜解决方案/京东用户购买意向预测/数据清洗.ipynb
new file mode 100644
index 0000000..8e5db25
--- /dev/null
+++ b/机器学习竞赛实战_优胜解决方案/京东用户购买意向预测/数据清洗.ipynb
@@ -0,0 +1,129 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 任务：京东用户购买意向预测"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 故事背景：\n",
+    "京东作为中国最大的自营式电商，在保持高速发展的同时，沉淀了数亿的忠实用户，积累了海量的真实数据。如何从历史数据中找出规律，去预测用户未来的购买需求，让最合适的商品遇见最需要的人，是大数据应用在精准营销中的关键问题，也是所有电商平台在做智能化升级时所需要的核心技术。\n",
+    "\n",
+    "以京东商城真实的用户、商品和行为数据（脱敏后）为基础，通过数据挖掘的技术和机器学习的算法，构建用户购买商品的预测模型，输出高潜用户和目标商品的匹配结果，为精准营销提供高质量的目标群体。\n",
+    "\n",
+    "目标：使用京东多个品类下商品的历史销售数据，构建算法模型，预测用户在未来5天内，对某个目标品类下商品的购买意向。"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 数据集：\n",
+    "这里涉及到的数据集是京东的数据集:\n",
+    "\n",
+    "* JData_User.csv 用户数据集 105,321个用户\n",
+    "* JData_Comment.csv 商品评论 558,552条记录\n",
+    "* JData_Product.csv 预测商品集合 24,187条记录\n",
+    "* JData_Action_201602.csv 2月份行为交互记录 11,485,424条记录\n",
+    "* JData_Action_201603.csv 3月份行为交互记录 25,916,378条记录\n",
+    "* JData_Action_201604.csv 4月份行为交互记录 13,199,934条记录"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**JData_User.csv用户数据**\n",
+    "\n",
+    "|字段|意义|备注|\n",
+    "|-|-|-|\n",
+    "|user_id|用户id|脱敏|\n",
+    "|age|年龄|-1表未知|\n",
+    "|sex|性别|0男，1女，2未知|\n",
+    "|user_lv_cd|用户等级|级别枚举，越高级别越大|\n",
+    "|user_reg_tm|用户注册日期|粒度到天|"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**JData_Comment.csv评论数据**\n",
+    "\n",
+    "|字段|意义|备注|\n",
+    "|-|-|-|\n",
+    "|dt|截止时间|天，到2016-02-01|\n",
+    "|sku_id|商品编号|脱敏|\n",
+    "|comment_num|累积评论数分段|0表示无评论，1表是1条，2表示2-10条，3表示11-50条，5表示大于50条|\n",
+    "|has_bad_comment|是否有差评|0表示无，1表示有|\n",
+    "|bad_comment_rate|差评率|差评数占总评论数的比率|"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**JData_Product.csv商品数据**\n",
+    "\n",
+    "|字段|意义|备注|\n",
+    "|-|-|-|\n",
+    "|sku_id|商品编号|脱敏|\n",
+    "|a1|属性1|枚举，-1表未知|\n",
+    "|a2|属性2|枚举，-1表未知|\n",
+    "|a3|属性3|枚举，-1表未知|\n",
+    "|cate|品牌ID|脱敏|\n",
+    "|brand|品牌ID|脱敏|"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**JData_Action_xx.csv商品数据**\n",
+    "\n",
+    "|字段|意义|备注|\n",
+    "|-|-|-|\n",
+    "|user_id|用户ID|脱敏|\n",
+    "|sku_id|商品编号|脱敏|\n",
+    "|time|行为时间||\n",
+    "|model_id|点击板块的编号|脱敏|\n",
+    "|type|行为类型|1.浏览商品详情页;2.加入购物车;3.购物车删除;4.下单;5.关注;6.点击;|\n",
+    "|cate|品牌ID|脱敏|\n",
+    "|brand|品牌ID|脱敏|"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}